Digital Commons Network^™

Frequency Of Low Impact Scores Among Adolescent And Young Adult Student-Athletes With Attention-Deficit/Hyperactivity Disorder And/Or Learning Disorder, Philip Schatz, John Cuzzupe, Justin E. Karr, Nathan E. Cook, Grant L. Iverson

Neurology Faculty Publications

Introduction: Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by attention problems, excessive activity, and impulsivity - occurring in approximately 13% of children 12– 17 years of age, and as many as 16% of older adolescents 18–22 years of age, with a greater prevalence in boys than girls. ADHD frequently co-occurs with specific learning disorder (LD), a neurodevelopmental disorder characterized by difficulties learning and using academic skills, such as reading, writing, and mathematics. Taken together, ADHD and/or LD are common among high school students and college students and can influence performance on computerized tests used in concussion management. However, normative …

Comparison Of Accuracy Of Different Dental Age Estimation Methods In Finnish And Turkish Populations, Aysima Darici, Merih Seval Olmez, H. Cem Güngör, Paivi Rajavaara, Annina Sipola, Vuokko Anttonen, Jari Pakkila

School of Dentistry Faculty Research and Publications

Objective: The aims of this study were to assess the accuracy of Cameriere’s and Demirjian’s methods in Finnish children, and compare the findings with those of the Turkish children according to dental age.

Material and methods: Dental panoramic tomography (DPT) of children (482 Finnish, 423 Turkish) aged between 5 and 15 years were evaluated. Comparison of mean difference between estimated and chronological age was evaluated. The difference between two means was analysed using paired t-test at 95% confidence interval (CI). Pearson correlation coefficients were used to estimate the correlation between chronological and estimated ages.

Results: Demirjian’s method resulted in …

Characterization Of Aromatic Stationary Phases For Uses In High Performance Liquid Chromatography, Anastasia Davis

Honors Theses

High Performance Liquid Chromatography (HPLC) is an analytical chemist technique used to separate a sample into its components to characterize and study a specific molecule or compound. Traditionally, High-Performance Liquid Chromatography in different industries, such as the environmental and pharmaceutical fields, uses stationary phases that are already well characterized, such as the C18 stationary phase for separation. However, aromatic stationary phases have recently been produced, which have phenyl groups bonded to the interior surface of the column. Still, they have not been well characterized because of how modern they are. This project characterized several aromatic stationary phases (Biphenyl, pentafluorophenyl, and …

Dementia Risk Reduction In The African Context: Multi-National Implementation Of Multimodal Strategies To Promote Healthy Brain Aging In Africa (The Africa-Fingers Project), Chinedu Momoh, Rachel Maina, Lukoye Atwoli, Karen Blackmon, Edna Bosire, Gloria Chemutai, Linda Khakali, Sylvia Mbugua, Zul Merali, Olivera Nesic Taylor,, Anthony Ngugi, Cyprian Mostert, Eunice Muthoni, Roselyter Riang’A, Mansoor Saleh, Shahin Sayed, Jasmit Shah

Brain and Mind Institute

Dementia prevention in Africa is critically underexplored, despite the continent's high prevalence of modifiable risk factors. With a predominantly young and middle-aged population, Africa presents a prime opportunity to implement evidence-based strategies that could significantly reduce future dementia cases and mitigate its economic impact. The multinational Africa-FINGERS program offers an innovative solution, pioneering culturally sensitive, multidomain interventions tailored to the unique challenges of the region. Leveraging insights from landmark global studies such as Worldwide-FINGERS and Alzheimer's Disease Neuroimaging Initiative, the program employs a multideterminant precision prevention framework, grounded in community based systems dynamics. Africa-FINGERS further integrates cutting-edge state-of-the-art multimodal biomarker …

Adverse Childhood Experiences And Hiv-Related Stigma: A Quantitative Survey Of Tanzanian Men, June 2019, Amandeep Kaur, Monique J. Brown Ph.D., Mph, Geoffrey K. Kangogo, Xiaoming Li Ph.D., Ivan E. Teri, Gaspar Mbita, Aima A. Ahonkhai, Donaldson F. Conserve

Faculty Publications

Experiencing adverse childhood experiences (ACEs) may impact personal opinions, attitudes, and judgments, which can further result in HIV-related stigma. HIV-related stigma consequentially may impact HIV preventive measures such as HIV testing, pre-exposure prophylaxis uptake, and condom use. The extent to which ACEs influence HIV-related stigma perception has not been well studied. Therefore, the study aimed to examine the association between ACEs and perceived and interpersonal HIV-related stigma among Tanzanian HIV-negative men. Quantitative survey data were obtained from the Tanzania STEP (Self-Testing Education and Promotion) project established in four wards: Mabibo, Manzese, Tandale, and Mwanyanamala. A total of 507 men responded …

Against The Substitutive Approach To Ai In Healthcare, Rand Hirmiz

Research Collection School of Social Sciences

Paul Bloom has famously argued against the need for empathy in clinicians, while Sally Dalton-Brown has argued that AI need not be capable of empathy to be a good carer. In this paper, the capacity for AI to substitute for human clinicians is assessed from a bioethical perspective, primarily through the evaluation of the arguments put forth by Dalton-Brown and Bloom concerning empathy in healthcare. In opposition to both Bloom and Dalton-Brown, this paper argues that (1) empathy is essential to providing good care or deep care (that is, care that goes beyond the mere fulfilment of medical tasks), (2) …

Fractionated Photoimmunotherapy Stimulates An Anti-Tumour Immune Response: An Integrated Mathematical And In Vitro Study, Mohammad U Zahid, Matthew Waguespack, Rebecca C Harman, Eric M Kercher, Shubhankar Nath, Tayyaba Hasan, Imran Rizvi, Bryan Q Spring, Heiko Enderling

Faculty, Staff and Student Publications

Background: Advanced epithelial ovarian cancer (EOC) has high recurrence rates due to disseminated initial disease presentation. Cytotoxic phototherapies, such as photodynamic therapy (PDT) and photoimmunotherapy (PIT, cell-targeted PDT), have the potential to treat disseminated malignancies due to safe intraperitoneal delivery.

Methods: We use in vitro measurements of EOC tumour cell and T cell responses to chemotherapy, PDT, and epidermal growth factor receptor targeted PIT as inputs to a mathematical model of non-linear tumour and immune effector cell interaction. The model outputs were used to calculate how photoimmunotherapy could be utilised for tumour control.

Results: In vitro measurements of PIT dose …

A Site-Wise Reliability Analysis Of The Abcd Diffusion Fractional Anisotropy And Cortical Thickness: Impact Of Scanner Platforms, Yezhi Pan, L Elliot Hong, Ashley Acheson, Paul M Thompson, Neda Jahanshad, Alyssa H Zhu, Jiaao Yu, Chixiang Chen, Tianzhou Ma, Ho-Ling Liu, Jelle Veraart, Els Fieremans, Nicole R Karcher, Peter Kochunov, Shuo Chen

Faculty, Staff and Student Publications

The Adolescent Brain and Cognitive Development (ABCD) project is the largest study of adolescent brain development. ABCD longitudinally tracks 11,868 participants aged 9-10 years from 21 sites using standardized protocols for multi-site MRI data collection and analysis. While the multi-site and multi-scanner study design enhances the robustness and generalizability of analysis results, it may also introduce nonbiological variances including scanner-related variations, subject motion, and deviations from protocols. ABCD imaging data were collected biennially within a period of ongoing maturation in cortical thickness and integrity of cerebral white matter. These changes can bias the classical test-retest methodologies, such as intraclass correlation …

Health Literacy And Perceived Control: Intermediary Factors In The Relationship Between Race And Cardiovascular Disease Risk In Incarcerated Men In The United States, Jennifer L. Miller, Misook L. Chung, Lovoria B. Williams, Alison R. Connell, Zyad T. Saleh, Abdullah S. Alhurani, Alison L. Bailey, Mary Kay Rayens, Debra K. Moser

UK CARES Faculty Publications

Background: Black race, inadequate health literacy, and poor perceived control are predictors of increased cardiovascular disease (CVD) risk. The purpose of this study was to explore the relationships among race, health literacy, perceived control, and CVD risk while controlling for known risk factors in incarcerated men. Methods: We included data from 349 incarcerated men to examine race and CVD risk (Framingham Risk Score) using a serial mediation model with health literacy and perceived control using 95% confidence intervals (CIs) from 5000 bootstrap samples. Results: Of the participants (age, 36 ± 10; education, 12 ± 2; body mass index, 28.3 ± …

Contrasting Association Pattern Of Plasma Low-Density Lipoprotein With White Matter Integrity In Apoe4 Carriers Versus Non-Carriers, Zhenyao Ye, Yezhi Pan, Rozalina G Mccoy, Chuan Bi, Chen Mo, Li Feng, Jiaao Yu, Tong Lu, Song Liu, J Carson Smith, Minxi Duan, Si Gao, Yizhou Ma, Chixiang Chen, Braxton D Mitchell, Paul M Thompson, L Elliot Hong, Peter Kochunov, Tianzhou Ma, Shuo Chen

Faculty, Staff and Student Publications

Apolipoprotein E ε4 (APOE4) is a strong genetic risk factor of Alzheimer’s disease and metabolic dysfunction. However, whether APOE4 and markers of metabolic dysfunction synergistically impact the deterioration of white matter (WM) integrity in older adults remains unknown.

In the UK Biobank data, we conducted a multivariate analysis to investigate the interactions between APOE4 and 249 plasma metabolites (measured using nuclear magnetic resonance spectroscopy) with whole-brain WM integrity (measured by diffusion-weighted magnetic resonance imaging) in a cohort of 1,917 older adults (aged 65.0–81.0 years; 52.4% female).

Although no main association was observed between either APOE4 or metabolites with …

Contactless And Scalable Approaches For Human Health And Performance Sensing, Ngoc Doan Thu Tran

Dissertations and Theses Collection (Open Access)

Human health and performance sensing has been extensively studied, from physiology to mental health and movement analytics. However, typical approaches rely on invasive and contact sensors or require professional practitioners, limiting their scalability. For example, the gold standard for measuring heart rate is through an electrocardiogram (ECG), which requires multiple probes attached to the skin and is impractical for individuals with skin issues. Additionally, it typically needs to be performed in a hospital setting under the supervision of a trained cardiac physiologist. Depression detection often relies on the expertise of psychologists or psychiatrists. However, there is a shortage of these …

National Use Of Artificial Intelligence For Eye Screening In Singapore, Dinesh Visva Gunasekeran, Steven Miller, Wynne Hsu, Mong Li, Tym Hon Wong, Mun Tuck Lee, Ecosse Lamoureau, Daniel Shu Wei Ting, Gavin Siew Wei Tan, Tien-Yin Wong

Research Collection School Of Computing and Information Systems

Diabetes is a major health care challenge, affecting 10% of the global population. One third of patients with diabetes have an ocular complication known as diabetic retinopathy (DR). DR progression to manifestations such as vision-threatening diabetic retinopathy (VTDR) remains the leading cause of blindness in working-aged adults. Yearly DR screening is a universally recommended practice in primary care settings for patients with diabetes, but it is often difficult to implement due to a lack of staffing and screening capacity in primary care. This case study highlights our experience with developing a medical artificial intelligence (AI) software-as-a-medical-device (SaMD) solution for DR …

Irl For Restless Multi-Armed Bandits With Applications In Maternal And Child Health, Gauri Jain, Pradeep Varakantham, Haifeng Xu, Aparna Taneja, Prashant Doshi, Milind Tambe

Research Collection School Of Computing and Information Systems

Public health practitioners often have the goal of monitoring patients and maximizing patients’ time spent in “favorable” or healthy states while being constrained to using limited resources. Restless multi-armed bandits (RMAB) are an effective model to solve this problem as they are helpful to allocate limited resources among many agents under resource constraints, where patients behave differently depending on whether they are intervened on or not. However, RMABs assume the reward function is known. This is unrealistic in many public health settings because patients face unique challenges and it is impossible for a human to know who is most deserving …

Toward A Responsible Future: Recommendations For Ai-Enabled Clinical Decision Support, Steven Labkoff, Bilikis Oladimeji, Joseph Kannry, Anthony Solomonides, Russell Leftwich, Eileen Koski, Amanda L Joseph, Monica Lopez-Gonzalez, Lee A Fleisher, Kimberly Nolen, Sayon Dutta, Deborah R Levy, Amy Price, Paul J Barr, Jonathan D Hron, Baihan Lin, Gyana Srivastava, Nuria Pastor, Unai Sanchez Luque, Tien Thi Thuy Bui, Reva Singh, Tayler Williams, Mark G Weiner, Tristan Naumann, Dean F Sittig, Gretchen Purcell Jackson, Yuri Quintana

Faculty, Staff and Student Publications

BACKGROUND: Integrating artificial intelligence (AI) in healthcare settings has the potential to benefit clinical decision-making. Addressing challenges such as ensuring trustworthiness, mitigating bias, and maintaining safety is paramount. The lack of established methodologies for pre- and post-deployment evaluation of AI tools regarding crucial attributes such as transparency, performance monitoring, and adverse event reporting makes this situation challenging.

OBJECTIVES: This paper aims to make practical suggestions for creating methods, rules, and guidelines to ensure that the development, testing, supervision, and use of AI in clinical decision support (CDS) systems are done well and safely for patients.

MATERIALS AND METHODS: In May …

An Artificial Intelligence-Generated Model Predicts 90-Day Survival In Alcohol-Associated Hepatitis: A Global Cohort Study, Winston Dunn, Yanming Li, Ashwani K Singal, Douglas A Simonetto, Luis A Díaz, Francisco Idalsoaga, Gustavo Ayares, Jorge Arnold, María Ayala-Valverde, Diego Perez, Jaime Gomez, Rodrigo Escarate, Eduardo Fuentes-López, Carolina Ramirez-Cadiz, Dalia Morales-Arraez, Wei Zhang, Steve Qian, Joseph C Ahn, Seth Buryska, Heer Mehta, Nicholas Dunn, Muhammad Waleed, Horia Stefanescu, Andreea Bumbu, Adelina Horhat, Bashar Attar, Rohit Agrawal, Joaquín Cabezas, Victor Echavaría, Berta Cuyàs, Maria Poca, German Soriano, Shiv K Sarin, Rakhi Maiwall, Prasun K Jalal, Fátima Higuera-De-La-Tijera, Anand V Kulkarni, P Nagaraja Rao, Patricia Guerra-Salazar, Lubomir Skladaný, Natália Kubánek, Veronica Prado, Ana Clemente-Sanchez, Diego Rincon, Tehseen Haider, Kristina R Chacko, Gustavo A Romero, Florencia D Pollarsky, Juan C Restrepo, Luis G Toro, Pamela Yaquich, Manuel Mendizabal, Maria L Garrido, Sebastián Marciano, Melisa Dirchwolf, Victor Vargas, César Jiménez, David Hudson, Guadalupe García-Tsao, Guillermo Ortiz, Juan G Abraldes, Patrick S Kamath, Marco Arrese, Vijay H Shah, Ramon Bataller, Juan Pablo Arab

Faculty, Staff and Students Publications

Background and aims: Alcohol-associated hepatitis (AH) poses significant short-term mortality. Existing prognostic models lack precision for 90-day mortality. Utilizing artificial intelligence in a global cohort, we sought to derive and validate an enhanced prognostic model.

Approach and results: The Global AlcHep initiative, a retrospective study across 23 centers in 12 countries, enrolled patients with AH per National Institute for Alcohol Abuse and Alcoholism criteria. Centers were partitioned into derivation (11 centers, 860 patients) and validation cohorts (12 centers, 859 patients). Focusing on 30 and 90-day postadmission mortality, 3 artificial intelligence algorithms (Random Forest, Gradient Boosting Machines, and eXtreme Gradient Boosting) …

Dna Methylation Classes Of Stage Ii And Iii Primary Melanomas And Their Clinical And Prognostic Significance, Kathleen Conway, Sharon N Edmiston, Amanda Vondras, Allison Reiner, David L Corcoran, Ronglai Shen, Eloise A Parrish, Honglin Hao, Lan Lin, Jessica M Kenney, Gbemisola Ilelaboye, Caroline E Kostrzewa, Pei Fen Kuan, Klaus J Busam, Cecilia Lezcano, Tim K Lee, Eva Hernando, Paul B Googe, David W Ollila, Stergios Moschos, Ivan Gorlov, Christopher I Amos, Marc S Ernstoff, Anne E Cust, James S Wilmott, Richard A Scolyer, Graham J Mann, Ismael A Vergara, Jennifer Ko, Judy R Rees, Shaofeng Yan, Eduardo Nagore, Marcus Bosenberg, Bonnie Gould Rothberg, Iman Osman, Jeffrey E Lee, Yvonne Saenger, Paul Bogner, Cheryl L Thompson, Meg Gerstenblith, Sheri L Holmen, Pauline Funchain, Elise Brunsgaard, Natalie D Depcik-Smith, Li Luo, Tawny Boyce, Irene Orlow, Colin B Begg, Marianne Berwick, Nancy E Thomas

Faculty, Staff and Students Publications

Purpose: Patients with stage II and III cutaneous primary melanoma vary considerably in their risk of melanoma-related death. We explore the ability of methylation profiling to distinguish primary melanoma methylation classes and their associations with clinicopathologic characteristics and survival.

Materials and methods: InterMEL is a retrospective case-control study that assembled primary cutaneous melanomas from American Joint Committee on Cancer (AJCC) 8th edition stage II and III patients diagnosed between 1998 and 2015 in the United States and Australia. Cases are patients who died of melanoma within 5 years from original diagnosis. Controls survived longer than 5 years without evidence of …

A Site-Wise Reliability Analysis Of The Abcd Diffusion Fractional Anisotropy And Cortical Thickness: Impact Of Scanner Platforms, Yezhi Pan, L Elliot Hong, Ashley Acheson, Paul M Thompson, Neda Jahanshad, Alyssa H Zhu, Jiaao Yu, Chixiang Chen, Tianzhou Ma, Ho-Ling Liu, Jelle Veraart, Els Fieremans, Nicole R Karcher, Peter Kochunov, Shuo Chen

2020-Current year OA Pubs

The Adolescent Brain and Cognitive Development (ABCD) project is the largest study of adolescent brain development. ABCD longitudinally tracks 11,868 participants aged 9-10 years from 21 sites using standardized protocols for multi-site MRI data collection and analysis. While the multi-site and multi-scanner study design enhances the robustness and generalizability of analysis results, it may also introduce nonbiological variances including scanner-related variations, subject motion, and deviations from protocols. ABCD imaging data were collected biennially within a period of ongoing maturation in cortical thickness and integrity of cerebral white matter. These changes can bias the classical test-retest methodologies, such as intraclass correlation …

Pushing The Boundaries Of Rare Disease Diagnostics With The Help Of The First Undiagnosed Hackathon, Angelica Maria Delgado-Vega, Helene Cederroth, Fulya Taylan, Katja Ekholm, Marlene Ek, Håkan Thonberg, Anders Jemt, Daniel Nilsson, Jesper Eisfeldt, Kristine Bilgrav Saether, Ida Höijer, Ozlem Akgun-Dogan, Yui Asano, Tahsin Stefan Barakat, Dominyka Batkovskyte, Gareth Baynam, Olaf Bodamer, Wanna Chetruengchai, Pádraic Corcoran, Madeline Couse, Daniel Danis, German Demidov, Eisuke Dohi, Mattias Erhardsson, Luis Fernandez-Luna, Toyofumi Fujiwara, Neha Garg, Roberto Giugliani, Claudia Gonzaga-Jauregui, Giedre Grigelioniene, Tudor Groza, Cecilia Gunnarsson, Anna Hammarsjö, Charles Kumi Hammond, Özden Hatirnaz Ng, Sirisha Hesketh, Dineshani Hettiarachchi, Maria Johansson Soller, Umn Ahmed Kirmani, Martin Kjellberg, Malin Kvarnung, Oleg Kvlividze, Kristina Lagerstedt-Robinson, Paul Lasko, Timo Lassmann, Lynette Y S Lau, Steven Laurie, Weng Khong Lim, Zhandong Liu, Mariya Lysenkova Wiklander, Prince Makay, Alassane Baneye Maiga, Carolina Maya-González, M Stephen Meyn, Ramprasad Neethiraj, Vincenzo Nigro, Felix Nordgren, Jessica Nordlund, Sara Orrsjö, Jesper Ottosson, Ugur Ozbek, Özkan Özdemir, Clyde Partin, David A Pearce, Raquel Peck, Annie Pedersen, Maria Pettersson, Monnat Pongpanich, Manuel Posada De La Paz, Arun Ramani, Juan Andres Romero, Vanessa I Romero, Richard Rosenquist, Aung Min Saw, Matthew Spencer, Eva-Lena Stattin, Chalurmpon Srichomthong, Isabel Tapia-Paez, Domenica Taruscio, Julie P Taylor, Tinatin Tkemaladze, Ian Tully, Zeynep Tümer, Wendy A G Van Zelst-Stams, Alain Verloes, Emma Västerviga, Sailan Wang, Rachel Yang, Shinya Yamamoto, Vicente A Yépez, Qing Zhang, Vorasuk Shotelersuk, Samuel Agyei Wiafe, Yasemin Alanay, Lorenzo D Botto, Salman Kirmani, Aimé Lumaka, Elizabeth Emma Palmer, Ratna Dua Puri, Valtteri Wirta, Anna Lindstrand, Orion J Buske, Mikk Cederroth, Ann Nordgren

Duncan NRI Faculty and Staff Publications

The first-ever Undiagnosed Hackathon was a groundbreaking event held by the Wilhelm Foundation, the Karolinska Undiagnosed Disease Program, and PhenoTips in collaboration with UDNI to solve medical mysteries and advance diagnostics for undiagnosed rare diseases. Nearly 100 healthcare professionals and researchers from 28 countries participated, working intensively for 48 hours to diagnose 10 families with undiagnosed rare diseases. This innovative approach to precision diagnostics highlighted the power of international, multidisciplinary collaboration and patient partnership, yielding promising results for patients seeking answers and benefiting the entire rare diseases community.

A Unique Case Of Cutaneous Melanoma: Case Report And Literature Review, Iulia Maria Teodora Leulescu, Grigore Bălan, Claudia Ioana Dogaru, Maria Moga, Emil Catalin Popa, Irina Popescu, Mircea Tampa, Simona Roxana Georgescu

Journal of Mind and Medical Sciences

Introduction. According to the European Cancer Information System, melanoma is the sixth most diagnosed cancer in Europe (following breast, colorectal, prostate, lung, and bladder cancer) and ranks among the top 20 most common causes of cancer-related death. The diagnosis of melanoma can be a clinical challenge due to the variety of signs and symptoms, ranging from small, asymptomatic lesions with slow progression to large, painful tumors with rapid growth. In this paper, we will report an exceptional case of cutaneous melanoma with an atypical presentation in a patient with no personal or family history of skin cancer. Case presentation. We …

Gastrointestinal Stromal Tumors: A Focus On The Impact Of Interstitial Cells Of Cajal In Disease Development, Petru Radu, Mihai Zurzu, Anca Tigora, Vlad Paic, Mircea Bratucu, Dragos Garofil, Valeriu Surlin, Stefan Patrascu, Virgiliu Prunoiu, Ionut Simion Coman, Valentin Georgescu, Razvan Daniel Chivu, Florian Popa, Victor Strambu, Raluca Gabriela Ioan

Journal of Mind and Medical Sciences

Introduction. Interstitial Cells of Cajal (ICCs) play a critical role in the regulation of gastrointestinal motility and have been implicated in various functional gastrointestinal disorders. Recent research indicates a possible association between ICCs and the tumor risk of Gastrointestinal Stromal Tumors (GISTs). This research aims to examine the clinical, histopathological, and biomolecular characteristics of ICCs and their relevance in assessing GIST risk. Materials and Methods. This study examined fourteen GIST patients who underwent surgical intervention at the Surgery Department of Carol Davila Nephrology Hospital in Bucharest. Parameters including age, gender, tumor location/ dimensions were scrutinized. Immunohistochemistry employing markers CD117, DOG-1, …

Artificial Intelligence And Liver Transplantation; Literature Review, Maria Serban, Irina Balescu, Sorin Petrea, Bogdan Gaspar, Lucian Pop, Valentin Varlas, Marilena Stoian, Camelia Diaconu, Cristian Balalau, Nicolae Bacalbasa

Journal of Mind and Medical Sciences

Liver transplantation is the last life-saving solution for patients with end stage liver disease. The discrepancy between waiting list and available organs has led to the appearance of extended donation criteria and the development of several scores (Child-Pugh score, MELD score, DRI score, SOFT score), in order to find the most suitable donor-recipient match. But none of these scores can predict survival after transplantation. Artificial Intelligence (AI) has recently been shown as an excellent tool for the study of the liver and comes in this aid with its various methods (random forest, artificial neural networks, decision tree, Bayesian networks, and …

The Santa Clara, 2024-10-31, Santa Clara University

The Santa Clara

No abstract provided.

Faktor Yang Berhubungan Pada Motivasi Pengguna Dan Implementasi Rekam Medis Elektronik Dengan Efisiensi Pelayanan Di Instalasi Rawat Jalan Rsud Kebayoran Lama, Jean Francis Melanny Kassiuw, Budi Hidayat

Jurnal ARSI : Administrasi Rumah Sakit Indonesia

Electronic Medical Records (EMR) have emerged as an innovative solution in healthcare because EMR offers several advantages and provides a comprehensive solution to improve health information management in today’s digital era. This study applies the Technology Acceptance Model (TAM) as its theoretical foundation, aiming to evaluate the relationship between user perceptions of key factors influencing EMR implementation and service efficiency in the Kebayoran Lama Regional Hospital outpatient unit. The research design is non-experimental with a quantitative approach, utilizing numerical data analyzed through Structural Equation Modeling (SEM). The study collected data on user perceptions regarding EMR implementation and service efficiency through …

Avoiding Common Pitfalls In Medical Writing: An Editor’S Advice, Deanna Erin Conners

Milne Open Textbooks

Avoiding Common Pitfalls in Medical Writing is a useful companion text to comprehensive style guides for the biomedical sciences. This book walks authors through best practices for writing scientific papers and grant proposals in a concise and accessible format. Authors and teachers worldwide will benefit from these shared insights of an experienced scientific editor.

Read this book online at: https://milnepublishing.geneseo.edu/medical-writing/

A Large Scale Multi Institutional Study For Radiomics Driven Machine Learning For Meningioma Grading, Mert Karabacak, Shiv Patil, Rui Feng, Raj K. Shrivastava, Konstantinos Margetis

Department of Medicine Faculty Papers

This study aims to develop and evaluate radiomics-based machine learning (ML) models for predicting meningioma grades using multiparametric magnetic resonance imaging (MRI). The study utilized the BraTS-MEN dataset's training split, including 698 patients (524 with grade 1 and 174 with grade 2-3 meningiomas). We extracted 4872 radiomic features from T1, T1 with contrast, T2, and FLAIR MRI sequences using PyRadiomics. LASSO regression reduced features to 176. The data was split into training (60%), validation (20%), and test (20%) sets. Five ML algorithms (TabPFN, XGBoost, LightGBM, CatBoost, and Random Forest) were employed to build models differentiating low-grade (grade 1) from high-grade …

Takotsubo Syndrome: An International Expert Consensus Report On Practical Challenges And Specific Conditions (Part-2: Specific Entities, Risk Stratification And Challenges After Recovery), Kenan Yalta, John E Madias, Nicholas G Kounis, Shams Y-Hassan, Marija Polovina, Servet Altay, Alexandre Mebazaa, Mehmet Birhan Yilmaz, Yuri Lopatin, Mamas A Mamas, Robert J Gil, Ritu Thamman, Abdallah Almaghraby, Biykem Bozkurt, Gani Bajraktari, Thomas Fink, Vassil Traykov, Stephane Manzo-Silberman, Ulvi Mirzoyev, Sekib Sokolovic, Zviad V Kipiani, Cecilia Linde, Petar M Seferovic

Faculty, Staff and Students Publications

Takotsubo syndrome (TTS) still remains as an enigmatic phenomenon. In particular, long-term challenges (including clinical recurrence and persistent symptoms) and specific entities in the setting of TTS have been the evolving areas of interest. On the other hand, a significant gap still exists regarding the proper risk-stratification of this phenomenon in the short and long terms. The present paper, the second part (part-2) of the consensus report, aims to discuss less well-known aspects of TTS including specific entities, challenges after recovery and risk-stratification.

Question Answering For Electronic Health Records: Scoping Review Of Datasets And Models, Jayetri Bardhan, Kirk Roberts, Daisy Zhe Wang

Faculty, Staff and Student Publications

Background: Question answering (QA) systems for patient-related data can assist both clinicians and patients. They can, for example, assist clinicians in decision-making and enable patients to have a better understanding of their medical history. Substantial amounts of patient data are stored in electronic health records (EHRs), making EHR QA an important research area. Because of the differences in data format and modality, this differs greatly from other medical QA tasks that use medical websites or scientific papers to retrieve answers, making it critical to research EHR QA.

Objective: This study aims to provide a methodological review of existing works on …

Moving Teamwork Into Teaming: Evaluating A Team-Based Model Of Nursing Care, Katie Lynn Maloney

Walden Dissertations and Doctoral Studies

Nursing practice faces staffing shortages, complex patient care, and a need to develop creative ways to fill staffing holes within the acute care clinical setting (Beckett et al., 2021). A hospital in New Hampshire, United States implemented a team-based nursing care model on a geriatric psychiatric unit in January 2023. The model has been in place for 18 months. The focus of this Doctor of Nursing Practice (DNP) quality improvement (QI) evaluation project was to determine if implementing the team-based nursing model of care improved patient outcomes such as falls, restraint use, and hospital-acquired pressure injuries and reduced the number …

Volumetric Ct Assessment Of In Situ Induced Hepatic Lesions In A Transgenic Swine Model, Derek Smetanick, Danielle Stolley, David Fuentes, Natalie W Fowlkes, Faith Shakoor, Maria Sophia Stenkamp, Samantha Hicks, Steve Parrish, Erik Cressman

Faculty, Staff and Student Publications

The growth rate of in situ-induced hepatic lesions in an Oncopig large animal model is quantitatively assessed. Oncopigs (n = 9) received baseline triple-phase CT scans prior to lesion induction. Lesions were subsequently induced by delivering the Ad-Cre vector to four locations in the liver. Triple-phase CT scans were obtained weekly to track the growth of the lesions. Animals were sacrificed at 14, 21, or 28 days (n = 3 in each group). The overall success rate of lesion generation was ~78%. Histopathology sections consistently revealed lesions that were highly inflammatory and consisted of a large leukocyte population without clear …

The Role Of Social Media Influencer In Bringing Economic Content Closer To Moroccan Youth -Youtube As An Example-, Mohammed Omar Zouhri

This study aims to monitor the effects of economic content published through the digital space in enhancing economic awareness among young people in Morocco, and empowering them with relevant knowledge and information in an attractive and simplified manner. The study begins by showing the extent to which young people, especially university students, interact with economic content through what social media influencers present on their YouTube channels. The study examines the nature of this content, its importance in bringing economic information closer to the public, and the extent of its ability to help a group of students improve their levels and …