Physical Sciences and Mathematics Commons^™

Triphlapan: Predicting Hla Molecules Binding Peptides Based On Triple Coding Matrix And Transfer Learning, Meng Wang, Chuqi Lei, Jianxin Wang, Yaohang Li, Min Li

Computer Science Faculty Publications

Human leukocyte antigen (HLA) recognizes foreign threats and triggers immune responses by presenting peptides to T cells. Computationally modeling the binding patterns between peptide and HLA is very important for the development of tumor vaccines. However, it is still a big challenge to accurately predict HLA molecules binding peptides. In this paper, we develop a new model TripHLApan for predicting HLA molecules binding peptides by integrating triple coding matrix, BiGRU + Attention models, and transfer learning strategy. We have found the main interaction site regions between HLA molecules and peptides, as well as the correlation between HLA encoding and binding …

Detection Of Tooth Position By Yolov4 And Various Dental Problems Based On Cnn With Bitewing Radiograph, Kuo Chen Li, Yi-Cheng Mao, Mu-Feng Lin, Yi-Qian Li, Chiung-An Chen, Tsung-Yi Chen, Patricia Angela R. Abu

Department of Information Systems & Computer Science Faculty Publications

Periodontitis is a high prevalence dental disease caused by bacterial infection of the bone that surrounds the tooth. Early detection and precision treatment can prevent more severe symptoms such as tooth loss. Traditionally, periodontal disease is identified and labeled manually by dental professionals. The task requires expertise and extensive experience, and it is highly repetitive and time-consuming. The aim of this study is to explore the application of AI in the field of dental medicine. With the inherent learning capabilities, AI exhibits remarkable proficiency in processing extensive datasets and effectively managing repetitive tasks. This is particularly advantageous in professions demanding …

Limitations Of Invasive Snake Control Tools In The Context Of A New Invasion On An Island With Abundant Prey, Shane R. Siers, Melia G. Nafus, Jereid E. Calaor, Rachel M. Volsteadt, Matthew S. Grassi, Megan Volsteadt, Aaron F. Collins, Patrick D. Barnhart, Logan T. Huse, Amy A. Yackel Adams, Diane L. Vice

USDA Wildlife Services: Staff Publications

In October 2020, a new population of invasive brown treesnakes (Boiga irregularis) was discovered on the 33-ha Cocos Island, 2.5 km off the south coast of Guam, United States. Cocos Island is a unique conservation resource, providing refuge for many lizards and birds, including endangered species, which were extirpated from mainland Guam by invasive predators including brown treesnakes. We sought to evaluate the usefulness of toxic baiting with acetaminophen-treated carrion baits and cage trapping, common tools for the control of brown treesnakes on mainland Guam, as potential eradication tools on Cocos Island. We evaluated multiple bait types and …

Decoding U.S. Tort Liability In Healthcare's Black-Box Ai Era: Lessons From The European Union, Mindy Duffourc, Sara Gerke

Faculty Scholarly Works

The rapid development of sophisticated artificial intelligence (“AI”) tools in healthcare presents new possibilities for improving medical treatment and general health. Currently, such AI tools can perform a wide range of health-related tasks, from specialized autonomous systems that diagnose diabetic retinopathy to general-use generative models like ChatGPT that answer users’ health-related questions. On the other hand, significant liability concerns arise as medical professionals and consumers increasingly turn to AI for health information. This is particularly true for black-box AI because while potentially enhancing the AI’s capability and accuracy, these systems also operate without transparency, making it difficult or even impossible …

Development Of A Regional Climate Change Model For Aedes Vigilax And Aedes Camptorhynchus (Diptera: Culicidae) In Perth, Western Australia, Kerry Staples, Peter J. Neville, Steven Richardson, Jacques Oosthuizen

Research outputs 2022 to 2026

Mosquito-borne disease is a significant public health issue and within Australia Ross River virus (RRV) is the most reported. This study combines a mechanistic model of mosquito development for two mosquito vectors; Aedes vigilax and Aedes camptorhynchus, with climate projections from three climate models for two Representative Concentration Pathways (RCPs), to examine the possible effects of climate change and sea-level rise on a temperate tidal saltmarsh habitat in Perth, Western Australia. The projections were run under no accretion and accretion scenarios using a known mosquito habitat as a case study. This improves our understanding of the possible implications of sea-level …

Identifying Patterns For Neurological Disabilities By Integrating Discrete Wavelet Transform And Visualization, Soo Yeon Ji, Sampath Jayarathna, Anne M. Perrotti, Katrina Kardiasmenos, Dong Hyun Jeong

Computer Science Faculty Publications

Neurological disabilities cause diverse health and mental challenges, impacting quality of life and imposing financial burdens on both the individuals diagnosed with these conditions and their caregivers. Abnormal brain activity, stemming from malfunctions in the human nervous system, characterizes neurological disorders. Therefore, the early identification of these abnormalities is crucial for devising suitable treatments and interventions aimed at promoting and sustaining quality of life. Electroencephalogram (EEG), a non-invasive method for monitoring brain activity, is frequently employed to detect abnormal brain activity in neurological and mental disorders. This study introduces an approach that extends the understanding and identification of neurological disabilities …

Machine Learning As A Tool For Early Detection: A Focus On Late-Stage Colorectal Cancer Across Socioeconomic Spectrums, Hadiza Galadima, Rexford Anson-Dwamena, Ashley Johnson, Ghalib Bello, Georges Adunlin, James Blando

Community & Environmental Health Faculty Publications

Purpose: To assess the efficacy of various machine learning (ML) algorithms in predicting late-stage colorectal cancer (CRC) diagnoses against the backdrop of socio-economic and regional healthcare disparities. Methods: An innovative theoretical framework was developed to integrate individual- and census tract-level social determinants of health (SDOH) with sociodemographic factors. A comparative analysis of the ML models was conducted using key performance metrics such as AUC-ROC to evaluate their predictive accuracy. Spatio-temporal analysis was used to identify disparities in late-stage CRC diagnosis probabilities. Results: Gradient boosting emerged as the superior model, with the top predictors for late-stage CRC diagnosis being anatomic site, …

Swosu Research And Scholarly Activity Fair 2024, Swosu Office Of Sponsored Programs

SWOSU Research and Scholarly Activity Fair Programs

On behalf of the members of the University Research and Scholarly Activity Committee (USRAC) and the Office of Sponsored Programs (OSP) at Southwestern Oklahoma State University (SWOSU) - Welcome to the Thirty-Second SWOSU Research and Scholarly Activity Fair! There are 61 poster presentations and 10 oral presentations involving over 100 student and faculty researchers, writers, presenters, artists, collaborators, and faculty sponsors encompassing activities from the SWOSU Departments of Biological Sciences, Chemistry & Physics, Engineering Technology, Kinesiology, Language & Literature, Mathematics, Music, Parks and Recreation Management, Pharmacy, Psychology, and Social Sciences.

Automatic Hemorrhage Segmentation In Brain Ct Scans Using Curriculum-Based Semi-Supervised Learning, Solayman H. Emon, Tzu-Liang (Bill) Tseng, Michael Pokojovy, Peter Mccaffrey, Scott Moen, Md Fashiar Rahman

Mathematics & Statistics Faculty Publications

One of the major neuropathological consequences of traumatic brain injury (TBI) is intracranial hemorrhage (ICH), which requires swift diagnosis to avert perilous outcomes. We present a new automatic hemorrhage segmentation technique via curriculum-based semi-supervised learning. It employs a pre-trained lightweight encoder-decoder framework (MobileNetV2) on labeled and unlabeled data. The model integrates consistency regularization for improved generalization, offering steady predictions from original and augmented versions of unlabeled data. The training procedure employs curriculum learning to progressively train the model at diverse complexity levels. We utilize the PhysioNet dataset to train and evaluate the proposed approach. The performance results surpass those of …

Predictive Power Of Wastewater For Nowcasting Infectious Disease Transmission: A Retrospective Case Study Of Five Sewershed Areas In Louisville, Kentucky, Fayette Klaassen, Rochelle H. Holm, Ted Smith, Ted Cohen, Aruni Bhatnagar, Nicolas A. Menzies

Faculty Scholarship

Background: Epidemiological nowcasting traditionally relies on count surveillance data. The availability and quality of such count data may vary over time, limiting representation of true infections. Wastewater data correlates with traditional surveillance data and may provide additional value for nowcasting disease trends. Methods: We obtained SARS-CoV-2 case, death, wastewater, and serosurvey data for Jefferson County, Kentucky (USA), between August 2020 and March 2021, and parameterized an existing nowcasting model using combinations of these data. We assessed the predictive performance and variability at the sewershed level and compared the effects of adding or replacing wastewater data to case and death reports. …

Infusing Machine Learning And Computational Linguistics Into Clinical Notes, Funke V. Alabi, Onyeka Omose, Omotomilola Jegede

Mathematics & Statistics Faculty Publications

Entering free-form text notes into Electronic Health Records (EHR) systems takes a lot of time from clinicians. A large portion of this paper work is viewed as a burden, which cuts into the amount of time doctors spend with patients and increases the risk of burnout. We will see how machine learning and computational linguistics can be infused in the processing of taking clinical notes. We are presenting a new language modeling task that predicts the content of notes conditioned on historical data from a patient's medical record, such as patient demographics, lab results, medications, and previous notes, with the …

Predicting The Need For Cardiovascular Surgery: A Comparative Study Of Machine Learning Models, Arman Ghavidel, Pilar Pazos, Rolando Del Aguila Suarez, Alireza Atashi

Engineering Management & Systems Engineering Faculty Publications

This research examines the efficacy of ensemble Machine Learning (ML) models, mainly focusing on Deep Neural Networks (DNNs), in predicting the need for cardiovascular surgery, a critical aspect of clinical decision-making. It addresses key challenges such as class imbalance, which is pivotal in healthcare settings. The research involved a comprehensive comparison and evaluation of the performance of previously published ML methods against a new Deep Learning (DL) model. This comparison utilized a dataset encompassing 50,000 patient records from a large hospital between 2015-2022. The study proposes enhancing the efficacy of these models through feature selection and hyperparameter optimization, employing techniques …

Toying With Adapted Toys, Joshua King

WWU Honors College Senior Projects

My project is a design for an adapted toy that occupational therapists (OT) can use when working with kids. OTs are people who help others to be able to do daily tasks that they need to do to live their lives. This can look like helping a person who has been injured or has a disability to accomplish tasks like getting dressed or feeding themselves. It can also involve helping school children to improve their writing or to use assistive technology. My project started out as an idea from my mom who is an OT and was using a coffee …

Quantification Of Antiviral Drug Tenofovir (Tfv) By Surface-Enhanced Raman Spectroscopy (Sers) Using Cumulative Distribution Functions (Cdfs), Marguerite R. Butler, Jana Hrncirova, Meredith Clark, Sucharita Dutta, John B. Cooper

Chemistry & Biochemistry Faculty Publications

Surface-enhanced Raman spectroscopy (SERS) is an ultrasensitive spectroscopic technique that generates signal-enhanced fingerprint vibrational spectra of small molecules. However, without rigorous control of SERS substrate active sites, geometry, surface area, or surface functionality, SERS is notoriously irreproducible, complicating the consistent quantitative analysis of small molecules. While evaporatively prepared samples yield significant SERS enhancement resulting in lower detection limits, the distribution of these enhancements along the SERS surface is inherently stochastic. Acquiring spatially resolved SERS spectra of these dried surfaces, we have shown that this enhancement is governed by a power law as a function of analyte concentration. Consequently, by definition, …

Evidence Of Direct Interaction Between Cisplatin And The Caspase-Cleaved Prostate Apoptosis Response-4 Tumor Suppressor, Krishna K. Raut, Samjhana Pandey, Gyanendra Kharel, Steven M. Pascal

Chemistry & Biochemistry Faculty Publications

Prostate apoptosis response-4 (Par-4) tumor suppressor protein has gained attention as a potential therapeutic target owing to its unique ability to selectively induce apoptosis in cancer cells, sensitize them to chemotherapy and radiotherapy, and mitigate drug resistance. It has recently been reported that Par-4 interacts synergistically with cisplatin, a widely used anticancer drug. However, the mechanistic details underlying this relationship remain elusive. In this investigation, we employed an array of biophysical techniques, including circular dichroism spectroscopy, dynamic light scattering, and UV–vis absorption spectroscopy, to characterize the interaction between the active caspase-cleaved Par-4 (cl-Par-4) fragment and cisplatin. Additionally, elemental analysis was …

Cumulative Distribution Function And Spatially Resolved Surface-Enhanced Raman Spectroscopy For The Quantitative Analysis Of Emtricitabine, Jana Hrncirova, Marguerite R. Butler, Sucharita Dutta, Meredith R. Clark, John B. Cooper

Chemistry & Biochemistry Faculty Publications

Surface-enhanced Raman spectroscopy (SERS) has exceptional analytical sensitivity and selectivity. However, SERS irreproducibility presents an obstacle when using it for precise quantitative measurements. In this study, colloidal nanoparticles evaporated to dryness are used as a SERS active surface for the detection of the HIV drug emtricitabine (FTC; trade name Emtriva). Despite the irreproducibility of the SERS resulting from the stochastic process of evaporation, using a SERS scanning instrument, the SERS enhancement factors of spatially resolved spectra have a well-defined distribution of signals for a given analyte concentration. This distribution follows a power law function ranging from weak (very abundant signals) …

Advancements In The Synthesis Of Polyoxygenated Oxepanes And Thiepanes For Applications To Natural Products, Aditya R. Pote, Shayne M. Weierbach, Mark W. Peczuh, Kyle M. Lambert

Chemistry & Biochemistry Faculty Publications

Oxepanes are central motifs and tenants of many biologically important molecules, and their synthetic construction often presents a challenge to chemists due to consequential entropic and enthalpic barriers that have limited the synthetic toolbox to access these seven-membered oxacycles. This review covers the breadth of synthetic methods to afford the oxepane/thiepane moiety, with a focus on polyoxygenated oxepanes and includes radical cyclizations, Lewis acid-mediated cyclizations, ring closing-metathesis, Nicholas-Ferrier rearrangement, homologations, and ring-expansion strategies. Implementation of these tactics towards sugar-based and non-sugar based (de novo) approaches is presented alongside their extensive application to the total synthesis of several complex polyoxygenated oxepane-containing …

Compton Scattering Of Mammographic Soft X-Ray Beams By Alkali And Transition Metal Salt Filters Produce X-Ray Interference Zones That May Have Treatment Potential For Localized Cancer Lesions, Subhendra N. Sarkar, Eric Lobel, Sabina Rakhmatova, Derbie Desir, Somdat Kissoon, Daler Djuraev, Katie Tam

Publications and Research

In breast x-ray imaging scattered radiation adds 50% of harmful radiation dose from anisotropic Compton scattering mechanism. We have been working with double layered inorganic salt materials that can induce Compton scattering to the incident mammographic x ray beams (in 20-30 kVp range) with adequate isotropy (angular control). Typically metal nitrates and alkali halide salt layers are shown here to cause low energy radiation interference zones with high and low photon intensities and local flux heterogeneity in terms of flux covariance. Spatial variation of low energy photon flux creates concentrated and sparse radiation zones that may be used to induce …

Locating Liability For Medical Ai, W. Nicholson Price Ii, I. Glenn Cohen

Articles

When medical AI systems fail, who should be responsible, and how? We argue that various features of medical AI complicate the application of existing tort doctrines and render them ineffective at creating incentives for the safe and effective use of medical AI. In addition to complexity and opacity, the problem of contextual bias, where medical AI systems vary substantially in performance from place to place, hampers traditional doctrines. We suggest instead the application of enterprise liability to hospitals—making them broadly liable for negligent injuries occurring within the hospital system—with an important caveat: hospitals must have access to the information needed …

Variables Affecting The Extraction Of Antioxidants In Cold And Hot Brew Coffee: A Review, Brian Yust, Frank Wilkinson, Niny Rao

College of Life Sciences Faculty Papers

Coffee beans are a readily available, abundant source of antioxidants used worldwide. With the increasing interest in and consumption of coffee beverages globally, research into the production, preparation, and chemical profile of coffee has also increased in recent years. A wide range of variables such as roasting temperature, coffee grind size, brewing temperature, and brewing duration can have a significant impact on the extractable antioxidant content of coffee products. While there is no single standard method for measuring all of the antioxidants found in coffee, multiple methods which introduce the coffee product to a target molecule or reagent can be …

Cabozantinib Plus Atezolizumab In Previously Untreated Advanced Hepatocellular Carcinoma And Previously Treated Gastric Cancer And Gastroesophageal Junction Adenocarcinoma: Results From Two Expansion Cohorts Of A Multicentre, Open-Label, Phase 1b Trial (Cosmic-021)., Daneng Li, Yohann Loriot, Adam Burgoyne, James Cleary, Armando Santoro, Daniel Lin, Santiago Ponce Aix, Ignacio Garrido-Laguna, Ramu Sudhagoni, Xiang Guo, Svetlana Andrianova, Scott Paulson

Kimmel Cancer Center Faculty Papers

BACKGROUND: Cabozantinib is approved for previously treated advanced hepatocellular carcinoma (aHCC) and has been investigated in gastric cancer (GC) and gastroesophageal junction adenocarcinoma (GEJ). Atezolizumab plus bevacizumab is approved for unresectable or metastatic HCC untreated with prior systemic therapy. We evaluated efficacy and safety of cabozantinib plus atezolizumab in aHCC previously untreated with systemic anticancer therapy or previously treated GC/GEJ.

METHODS: COSMIC-021 (ClinicalTrials.gov, NCT03170960) is an open-label, phase 1b study in solid tumours with a dose-escalation stage followed by tumour-specific expansion cohorts, including aHCC (cohort 14) and GC/GEJ (cohort 15). Eligible patients were aged ≥18 years with measurable locally advanced, …

Prt543, A Protein Arginine Methyltransferase 5 Inhibitor, In Patients With Advanced Adenoid Cystic Carcinoma: An Open-Label, Phase I Dose-Expansion Study, Renata Ferrarotto, Paul Swiecicki, Dan Zandberg, Robert Baiocchi, Robert Wesolowski, Cristina Rodriguez, Meredith Mckean, Hyunseok Kang, Varun Monga, Rajneesh Nath, Neil Palmisiano, Naveen Babbar, William Sun, Glenn Hanna

Department of Medical Oncology Faculty Papers

OBJECTIVES: Currently, no systemic treatments are approved for patients with recurrent and/or metastatic (R/M) adenoid cystic carcinoma (ACC). PRT543, a protein arginine methyltransferase 5 inhibitor that downregulates NOTCH1 and MYB signalling in tumours, is a potential candidate for R/M ACC treatment. We report the safety, tolerability and preliminary efficacy of PRT543 in a dose-expansion cohort of patients with R/M ACC.

MATERIALS AND METHODS: This phase I multicentre, open-label, sequential-cohort, dose-escalation and dose-expansion study (NCT03886831) enrolled patients with advanced solid tumours and select haematologic malignancies. Dose-escalation study design and results were reported previously. In the dose expansion, patients with R/M ACC …

Stereotactic Mr-Guided On-Table Adaptive Radiation Therapy (Smart) For Borderline Resectable And Locally Advanced Pancreatic Cancer: A Multi-Center, Open-Label Phase 2 Study, Michael Chuong, Percy Lee, Daniel Low, Joshua Kim, Kathryn Mittauer, Michael Bassetti, Carri Glide-Hurst, Ann Raldow, Yingli Yang, Lorraine Portelance, Kyle Padgett, Bassem Zaki, Rongxiao Zhang, Hyun Kim, Lauren Henke, Alex Price, Joseph Mancias, Christopher Williams, John Ng, Ryan Pennell, M Raphael Pfeffer, Daphne Levin, Adam Mueller, Karen Mooney, Patrick Kelly, Amish Shah, Luca Boldrini, Lorenzo Placidi, Martin Fuss, Parag Jitendra Parikh

Department of Radiation Oncology Faculty Papers

BACKGROUND AND PURPOSE: Radiation dose escalation may improve local control (LC) and overall survival (OS) in select pancreatic ductal adenocarcinoma (PDAC) patients. We prospectively evaluated the safety and efficacy of ablative stereotactic magnetic resonance (MR)-guided adaptive radiation therapy (SMART) for borderline resectable (BRPC) and locally advanced pancreas cancer (LAPC). The primary endpoint of acute grade ≥ 3 gastrointestinal (GI) toxicity definitely related to SMART was previously published with median follow-up (FU) 8.8 months from SMART. We now present more mature outcomes including OS and late toxicity.

MATERIALS AND METHODS: This prospective, multi-center, single-arm open-label phase 2 trial (NCT03621644) enrolled 136 …

Mutational Analysis Of The Nitrogenase Carbon Monoxide Protective Protein Cown Reveals That A Conserved C‑Terminal Glutamic Acid Residue Is Necessary For Its Activity, Dustin L. Willard, Joshuah J. Arellano, Mitch Underdahl, Terrence M. Lee, Avinash S. Ramaswamy, Gabriella Fumes, Agatha Kliman, Emily Y. Wong, Cedric P. Owens

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Nitrogenase is the only enzyme that catalyzes the reduction of nitrogen gas into ammonia. Nitrogenase is tightly inhibited by the environmental gas carbon monoxide (CO). Many nitrogen fixing bacteria protect nitrogenase from CO inhibition using the protective protein CowN. This work demonstrates that a conserved glutamic acid residue near the C-terminus of Gluconacetobacter diazotrophicus CowN is necessary for its function. Mutation of the glutamic acid residue abolishes both CowN’s protection against CO inhibition and the ability of CowN to bind to nitrogenase. In contrast, a conserved C-terminal cysteine residue is not important for CO protection by CowN. Overall, this work …

Deep Learning Uncertainty Quantification For Clinical Text Classification, Alina Peluso, Ioana Danciu, Hong-Jun Yoon, Jamaludin Mohd Yusof, Tanmoy Bhattacharya, Adam Spannaus, Noah Schaefferkoetter, Eric B. Durbin, Xiao-Cheng Wu, Antoinette Stroup, Jennifer Doherty, Stephen Schwartz, Charles Wiggins, Linda Coyle, Lynne Penberthy, Georgia D. Tourassi, Shang Gao

School of Public Health Faculty Publications

INTRODUCTION: Machine learning algorithms are expected to work side-by-side with humans in decision-making pipelines. Thus, the ability of classifiers to make reliable decisions is of paramount importance. Deep neural networks (DNNs) represent the state-of-the-art models to address real-world classification. Although the strength of activation in DNNs is often correlated with the network's confidence, in-depth analyses are needed to establish whether they are well calibrated. METHOD: In this paper, we demonstrate the use of DNN-based classification tools to benefit cancer registries by automating information extraction of disease at diagnosis and at surgery from electronic text pathology reports from the US National …

The Dose-Response Effect Of Aerobic Exercise On Inflammation In Colon Cancer Survivors, Justin C. Brown, Stephanie L.E. Compton, Jeffrey A. Meyerhardt, Guillaume Spielmann, Shengping Yang

School of Medicine Faculty Publications

Background; Physical activity after surgical resection for colon cancer is associated with significantly longer disease-free survival. Inflammation is hypothesized to mediate the association between physical activity and disease-free survival in colon cancer. Methods; In this exploratory analysis of a randomized dose-response trial, 39 colon cancer survivors who completed standard therapy were stratified by cancer stage and randomized in a 1;1;1 ratio to one of three treatment groups for 24 weeks of usual-care control, 150 min/wk of moderate-intensity aerobic exercise (low-dose), or 300 min/wk of moderate-intensity aerobic exercise (high-dose). Inflammation outcomes included high-sensitivity C-reactive protein (hs-CRP), interleukin-6 (IL6), and soluble tumor …

Raman Spectroscopic Analysis Of Human Serum Samples Of Convalescing Covid-19 Positive Patients, Hugh Byrne, Naomi Jackson, Jaythoon Hassan

Articles

Rapid screening, detection and monitoring of viral infection is of critical importance, as exemplified by the rapid spread of SARS-CoV-2, leading to the worldwide pandemic of COVID-19. This is equally the case for the stages of patient convalescence as for the initial stages of infection, to understand the medium and long terms effects, as well as the efficacy of therapeutic interventions. Optical spectroscopic techniques potentially offer an alternative to currently employed techniques of screening for the presence, or the response to infection. In this study, the ability of Raman spectroscopy to distinguish between samples of the serum of convalescent COVID-19 …

The Impact Of Neighborhood Socioeconomic Disadvantage On Operative Outcomes After Single-Level Lumbar Fusion, Grace Y. Ng, Ritesh Karsalia, Ryan S. Gallagher, Austin J. Borja, Jianbo Na, Scott Mcclintock, Neil R. Malhotra

Mathematics Faculty Publications

INTRODUCTION: The relationship between socioeconomic status and neurosurgical outcomes has been investigated with respect to insurance status or median household income, but few studies have considered more comprehensive measures of socioeconomic status. This study examines the relationship between Area Deprivation Index (ADI), a comprehensive measure of neighborhood socioeconomic disadvantage, and short-term postoperative outcomes after lumbar fusion surgery. METHODS: 1861 adult patients undergoing single-level, posterior-only lumbar fusion at a single, multihospital academic medical center were retrospectively enrolled. An ADI matching protocol was used to identify each patient's 9-digit zip code and the zip code-associated ADI data. Primary outcomes included 30- and …

Models Of Shared Care For The Management Of Psychotic Disorder After First Diagnosis In Ontario., Joshua C. Wiener, Rebecca Rodrigues, Jennifer N S Reid, Kelly K. Anderson

Epidemiology and Biostatistics Publications

OBJECTIVE: To describe the provision of care for young people following first diagnosis of psychotic disorder.

DESIGN: Retrospective cohort study using health administrative data.

SETTING: Ontario.

PARTICIPANTS: People aged 14 to 35 years with a first diagnosis of nonaffective psychotic disorder in Ontario between 2005 and 2015 (N=39,449).

MAIN OUTCOME MEASURES: Models of care, defined by psychosis-related service contacts with primary care physicians and psychiatrists during the 2 years after first diagnosis of psychotic disorder.

RESULTS: During the 2-year follow-up period, 29% of the cohort received only primary care, 30% received only psychiatric care, and 32% received both primary and …

Self-Supervised Pseudo Multi-Class Pre-Training For Unsupervised Anomaly Detection And Segmentation In Medical Images, Yu Tian, Fengbei Liu, Guansong Pang, Yuanhong Chen, Yuyuan Liu, Johan W. Verjans, Rajvinder Singh, Gustavo Carneiro

Research Collection School Of Computing and Information Systems

Unsupervised anomaly detection (UAD) methods are trained with normal (or healthy) images only, but during testing, they are able to classify normal and abnormal (or disease) images. UAD is an important medical image analysis (MIA) method to be applied in disease screening problems because the training sets available for those problems usually contain only normal images. However, the exclusive reliance on normal images may result in the learning of ineffective low-dimensional image representations that are not sensitive enough to detect and segment unseen abnormal lesions of varying size, appearance, and shape. Pre-training UAD methods with self-supervised learning, based on computer …