Medicine and Health Sciences Commons^™

Artificial Intelligence In Neuroradiology: A Scoping Review Of Some Ethical Challenges, Pegah Khosravi, Mark Schweitzer

Publications and Research

Artificial intelligence (AI) has great potential to increase accuracy and efficiency in many aspects of neuroradiology. It provides substantial opportunities for insights into brain pathophysiology, developing models to determine treatment decisions, and improving current prognostication as well as diagnostic algorithms. Concurrently, the autonomous use of AI models introduces ethical challenges regarding the scope of informed consent, risks associated with data privacy and protection, potential database biases, as well as responsibility and liability that might potentially arise. In this manuscript, we will first provide a brief overview of AI methods used in neuroradiology and segue into key methodological and ethical challenges. …

The Compound Risk Of Heat And Covid-19 In New York City: Riskscapes, Physical And Social Factors, And Interventions, Janelle Knox-Hayes, Juan Camilo Osorio, Natasha Stamler, Maria Dombrov, Rose Winer, Mary Hannah Smith, Reginald Blake, Cynthia Rosenzweig

Publications and Research

Climate change is disrupting the fundamental conditions of human life and exacerbating existing inequity by placing further burdens on communities that are already vulnerable. Risk exposure varies by where people live and work. In this article, we examine the spatial overlap of the compound risks of COVID-19 and extreme heat in New York City. We assess the relationship between socio-demographic and natural, built and social environmental characteristics, and the spatial correspondence of COVID-19 daily case rates across three pandemic waves. We use these data to create a compound risk index combining heat, COVID-19, density and social vulnerability. Our findings demonstrate …

Artificial Intelligence And The Situational Rationality Of Diagnosis: Human Problem-Solving And The Artifacts Of Health And Medicine, Michael W. Raphael

Publications and Research

What is the problem-solving capacity of artificial intelligence (AI) for health and medicine? This paper draws out the cognitive sociological context of diagnostic problem-solving for medical sociology regarding the limits of automation for decision-based medical tasks. Specifically, it presents a practical way of evaluating the artificiality of symptoms and signs in medical encounters, with an emphasis on the visualization of the problem-solving process in doctor-patient relationships. In doing so, the paper details the logical differences underlying diagnostic task performance between man and machine problem-solving: its principle of rationality, the priorities of its means of adaptation to abstraction, and the effects …

Toward Informatics-Enabled Preparedness For Natural Hazards To Minimize Health Impacts Of Climate Change, Jimmy Phuong, Naomi O. Riches, Luca Calzoni, Gora Datta, Deborah Duran, Asiyah Yu Lin, Ramesh P. Singh, Anthony E. Solomonides, Noreen Y. Whysel, Ramakanth Kavuluru

Publications and Research

Natural hazards (NHs) associated with climate change have been increasing in frequency and intensity. These acute events impact humans both directly and through their effects on social and environmental determinants of health. Rather than relying on a fully reactive incident response disposition, it is crucial to ramp up preparedness initiatives for worsening case scenarios. In this perspective, we review the landscape of NH effects for human health and explore the potential of health informatics to address associated challenges, specifically from a preparedness angle. We outline important components in a health informatics agenda for hazard preparedness involving hazard-disease associations, social determinants …

Diagnosis Of Polypoidal Choroidal Vasculopathy From Fluorescein Angiography Using Deep Learning, Yu-Yeh Tsai, Wei-Yang Ling, Shih-Jen Chen, Paisan Ruamviboonsuk, Cheng-Ho King, Chia-Ling Tsai

Publications and Research

Purpose: To differentiate polypoidal choroidal vasculopathy (PCV) from choroidal neovascularization (CNV) and to determine the extent of PCV from fluorescein angiography (FA) using attention-based deep learning networks.

Methods: We build two deep learning networks for diagnosis of PCV using FA, one for detection and one for segmentation. Attention-gated convolutional neural network (AG-CNN) differentiates PCV from other types of wet age-related macular degeneration. Gradient-weighted class activation map (Grad-CAM) is generated to highlight important regions in the image for making the prediction, which offers explainability of the network. Attention-gated recurrent neural network (AG-PCVNet) for spatiotemporal prediction is applied for segmentation …

Diagnosis Of Polypoidal Choroidal Vasculopathy From Fluorescein Angiography Using Deep Learning, Yu-Yeh Tsai, Wei-Yang Lin, Shih-Jen Chen, Paisan Ruamviboonsuk, Cheng-Ho King, Chia-Ling Tsai

Publications and Research

Purpose: To differentiate polypoidal choroidal vasculopathy (PCV) from choroidal neovascularization (CNV) and to determine the extent of PCV from fluorescein angiography (FA) using attention-based deep learning networks.

Methods: We build two deep learning networks for diagnosis of PCV using FA, one for detection and one for segmentation. Attention-gated convolutional neural network (AG-CNN) differentiates PCV from other types of wet age-related macular degeneration. Gradient-weighted class activation map (Grad-CAM) is generated to highlight important regions in the image for making the prediction, which offers explainability of the network. Attention-gated recurrent neural network (AG-PCVNet) for spatiotemporal prediction is applied for segmentation of PCV. …

Biomedical Applications Of Lanthanide Nanomaterials, For Imaging, Sensing And Therapy, Qize Zhang, Stephen O'Brien, Jan Grimm

Publications and Research

The application of nanomaterials made of rare earth elements within biomedical sciences continues to make significant progress. The rare earth elements, also called the lanthanides, play an essential role in modern life through materials and electronics. As we learn more about their utility, function, and underlying physics, we can contemplate extending their applications to biomedicine. This particularly applies to diagnosis and radiation therapy due to their relatively unique features, such as an ultra-wide Stokes shift in the luminescence, variable magnetism and potentially tunable properties, due to the library of lanthanides available and their multivalent oxidation state chemistry. The ability to …

Behavioral Predictive Analytics Towards Personalization For Self-Management – A Use Case On Linking Health-Related Social Needs, Bon Sy, Michael Wassil, Helene Connelly, Alisha Hassan

Publications and Research

The objective of this research is to investigate the feasibility of applying behavioral predictive analytics to optimize patient engagement in diabetes self-management, and to gain insights on the potential of infusing a chatbot with NLP technology for discovering health-related social needs. In the U.S., less than 25% of patients actively engage in self-health management even though self-health management has been reported to associate with improved health outcomes and reduced healthcare costs. The proposed behavioral predictive analytics relies on manifold clustering to identify subpopulations segmented by behavior readiness characteristics that exhibit non-linear properties. For each subpopulation, an individualized auto-regression model and …

Automatic Cephalometric Landmark Detection On X-Ray Images Using Object Detection, Cheng-Ho King, Yin-Lin Wang, Chia-Ling Tsai

Publications and Research

We propose a new deep convolutional cephalometric landmark detection framework for orthodontic treatment. Our proposed method consists of two major steps: landmark detection using a deep neural network for object detection, and landmark repair to ensure one instance per landmark class. For landmark detection, we modify the loss function of the backbone network YOLOv3 to eliminate the constrains on the bounding box and incorporate attention mechanism to improve the detection accuracy. For landmark repair, a triangle mesh is generated from the average face to eliminate superfluous instances, followed by estimation of missing landmarks from the detected ones using Laplacian Mesh. …

Treatment Selection Using Prototyping In Latent-Space With Application To Depression Treatment, Akiva Kleinerman, Ariel Rosenfeld, David Benrimoh, Robert Fratila, Caitrin Armstrong, Joseph Mehltretter, Eliyahu Shneider, Amit Yaniv-Rosenfeld, Jordan Karp, Charles F. Reynolds, Gustavo Turecki, Adam Kapelner

Publications and Research

Machine-assisted treatment selection commonly follows one of two paradigms: a fully personalized paradigm which ignores any possible clustering of patients; or a sub-grouping paradigm which ignores personal differences within the identified groups. While both paradigms have shown promising results, each of them suffers from important limitations. In this article, we propose a novel deep learning-based treatment selection approach that is shown to strike a balance between the two paradigms using latent-space prototyping. Our approach is specifically tailored for domains in which effective prototypes and sub-groups of patients are assumed to exist, but groupings relevant to the training objective are not …

The Temperature-Dependent Conformational Ensemble Of Sars-Cov-2 Main Protease (Mpro), Ali Ebrahim, Blake T. Riley, Desigan Kumaran, Babak Andi, Martin R. Fuchs, Sean Mcsweeney, Daniel A. Keedy

Publications and Research

The COVID-19 pandemic, instigated by the SARS-CoV-2 coronavirus, continues to plague the globe. The SARS-CoV-2 main protease, or M^pro, is a promising target for development of novel antiviral therapeutics. Previous X-ray crystal structures of M^pro were obtained at cryogenic temperature or room temperature only. Here we report a series of high-resolution crystal structures of unliganded M^pro across multiple temperatures from cryogenic to physiological, and another at high humidity. We interrogate these datasets with parsimonious multiconformer models, multi-copy ensemble models, and isomorphous difference density maps. Our analysis reveals a temperature-dependent conformational landscape for M^pro, including …

Decoding Clinical Biomarker Space Of Covid-19: Exploring Matrix Factorization-Based Feature Selection Methods, Farshad Saberi-Movahed, Mahyar Mohammadifard, Adel Mehrpooya, Mohammad Rezaei-Ravari, Kamal Berahmand, Mehrdad Rostami, Saeed Karami, Mohammad Najafzadeh, Davood Hajinezhad, Mina Jamshidi, Farshid Abedi, Mahtab Mohammadifard, Elnaz Farbod, Farinaz Safavi, Mohammadreza Dorvash, Shahrzad Vahedi, Mahdi Eftekhari, Farid Saberi-Movahed, Iman Tavassoly

Publications and Research

One of the most critical challenges in managing complex diseases like COVID-19 is to establish an intelligent triage system that can optimize the clinical decision-making at the time of a global pandemic. The clinical presentation and patients’ characteristics are usually utilized to identify those patients who need more critical care. However, the clinical evidence shows an unmet need to determine more accurate and optimal clinical biomarkers to triage patients under a condition like the COVID-19 crisis. Here we have presented a machine learning approach to find a group of clinical indicators from the blood tests of a set of COVID-19 …

Pattern Of Use Of Electronic Health Record (Ehr) Among The Chronically Ill: A Health Information National Trend Survey (Hints) Analysis, Rose Calixte, Sumaiya Islam, Zainab Toteh Osakwe, Argelis Rivera, Marlene Camacho-Rivera

Publications and Research

Effective patient–provider communication is a cornerstone of patient-centered care. Patient portals provide an effective method for secure communication between patients or their proxies and their health care providers. With greater acceptability of patient portals in private practices, patients have a unique opportunity to manage their health care needs. However, studies have shown that less than 50% of patients reported accessing the electronic health record (EHR) in a 12-month period. We used HINTS 5 cycle 1 and cycle 2 to assess disparities among US residents 18 and older with any chronic condition regarding the use of EHR for secure direct messaging …

Covid-19 Impact On Radiology Students’ Distance Learning (Summer 2021), Mary Lee, Jason Chan, Cheryann Jackson-Holmes, Renzo Marmolejo, Zoya Vinokur

Publications and Research

The Radiological Technology students have adjusted from the urgent distance learning that was enacted in the Spring of 2020, to the hybrid distance learning that is currently in place. This hybrid distance learning is the same way the incoming class of radiological technology students were taught. Both cohorts of students were tracked over the year by online anonymous surveys. We wanted to know how students were adapting to distance learning, if their focus and motivation varied over the course of the year due to changing pandemic conditions. For the students that were working, what impact did it have on their …

Covid-19 Multi-Targeted Drug Repurposing Using Few-Shot Learning, Yang Liu, You Wu, Xiaoke Shen, Lei Xie

Publications and Research

The life-threatening disease COVID-19 has inspired significant efforts to discover novel therapeutic agents through repurposing of existing drugs. Although multi-targeted (polypharmacological) therapies are recognized as the most efficient approach to system diseases such as COVID-19, computational multi-targeted compound screening has been limited by the scarcity of high-quality experimental data and difficulties in extracting information from molecules. This study introduces MolGNN , a new deep learning model for molecular property prediction. MolGNN applies a graph neural network to computational learning of chemical molecule embedding. Comparing to state-of-the-art approaches heavily relying on labeled experimental data, our method achieves equivalent or superior prediction …

Intangible Cultural Heritage: A Benefit To Climate-Displaced And Host Communities, Gül Aktürk, Martha B. Lerski

Publications and Research

Climate change is borderless, and its impacts are not shared equally by all communities. It causes an imbalance between people by creating a more desirable living environment for some societies while erasing settlements and shelters of some others. Due to floods, sea level rise, destructive storms, drought, and slow-onset factors such as salinization of water and soil, people lose their lands, homes, and natural resources. Catastrophic events force people to move voluntarily or involuntarily. The relocation of communities is a debatable climate adaptation measure which requires utmost care with human rights, ethics, and psychological well-being of individuals upon the issues …

Interfacial Dynamics And Ionic Transport Of Radiologic Contrast Media In Carbohydrate Matrix: Utility And Limits Of X-Ray Imaging, Lin Mousa, Hayley Sanchez, Subhendra Sarkar, Zoya Vinokur

Publications and Research

Hello, our names are Lin Mousa and Hayley Sanchez, this semester we participated in a research project dedicated to analyzing the interactions of contrast media with the molecular components of fruits to compare how they would react with the human brain. This project involved the injection of fruits with varying contrasts and the imaging of the diffusion and interactions of the contrast within the fruits with X-rays. With setup technical parameters on the x-ray equipment images were taken with identical setups at an hourly rate for several days. The final results of this experiment indicated that contrasts such as Gadolinium …

Human Ace2‑Functionalized Gold “Virus‑Trap” Nanostructures For Accurate Capture Of Sars‑Cov‑2 And Single‑Virus Sers Detection, Yong Yang, Yusi Peng, Chenglong Lin, Li Long, Jingying Hu, Jun He, Hui Zeng, Zhengren Huang, Zhi-Yuan Li, Masaki Tanemura, Jianlin Shi, John R. Lombardi, Xiaoying Luo

Publications and Research

The current COVID-19 pandemic urges the extremely sensitive and prompt detection of SARS-CoV-2 virus. Here, we present a Human Angiotensin-converting-enzyme 2 (ACE2)-functionalized gold “virus traps” nanostructure as an extremely sensitive SERS biosensor, to selectively capture and rapidly detect S-protein expressed coronavirus, such as the current SARS-CoV-2 in the contaminated water, down to the single-virus level. Such a SERS sensor features extraordinary 106- fold virus enrichment originating from high-affinity of ACE2 with S protein as well as “virus-traps” composed of oblique gold nanoneedles, and 109- fold enhancement of Raman signals originating from multicomponent SERS effects. Furthermore, the identification standard of virus …

Understanding Of Aerosol Transmission Of Covid 19 In Indoor Environments, Adama Barro, Cathal O'Toole, Jacob S. Lopez, Matthew Quinones, Sherene Moore

Publications and Research

Our reason for discussing severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) or 2019 novel corona virus (Covid-19), is to understand its aerosol transmission characteristics in indoor spaces and to mitigate further spread of this disease by designing a new HVAC system. The problem that we are tackling is the spread of covid-19 droplets through aerosol transmission by looking at potential engineering solutions to the existing HVAC systems. The purpose is to eradicate the spread of the COVID-19 by testing indoor spaces in an effort to understand the effectiveness of ventilation controls. We believe that scientists and engineers have not …

Protocol For A National Probability Survey Using Home Specimen Collection Methods To Assess Prevalence And Incidence Of Sars-Cov-2 Infection And Antibody Response, Aaron J. Siegler, Patrick S. Sullivan, Travis Sanchez, Ben Lopman, Mansour Fahimi, Charles Sailey, Martin Frankel, Richard Rothenberg, Colleen F. Kelley, Heather Bradley

Publications and Research

Purpose: The U.S. response to the SARS-CoV-2 epidemic has been hampered by early and ongoing delays in testing for infection; without data on where infections were occurring and the magnitude of the epidemic, early public health responses were not data-driven. Understanding the prevalence of SARSCoV- 2 infections and immune response is critical to developing and implementing effective public health responses. Most serological surveys have been limited to localities that opted to conduct them and/or were based on convenience samples. Moreover, results of antibody testing might be subject to high false positive rates in the setting of low prevalence of immune …

Mapping Gadolinium Contrast In A Complex Ionic And Photosynthesis Environment Of Pineapple By Near-Infrared And X-Ray Imaging, Subhendra Sarkar, Zoya Vinokur, Chen Xu, Tetiana Soloviova, Amina Shahbaz, Aldona Gjoni

Publications and Research

This work explores the diffusivity of a lanthanide complex, Eovist (Gadolinium-Ethoxy Benzyl Diethylenetriamine pentaacetate) that is stable in neutral media but is not in acidic environment. In the current work an acidic fruit model like pineapple that is rich in transition metals was used and a possible transmetallation reaction among Eovist and transition metal complexes was tested using X-ray imaging. Another goal of this work was to perturb the usual and the unusual photosynthesis systems that pineapple has maintained for millions of years during the evolution of circadian genes for efficient water conservation by dark photosynthesis. To detect such photosynthesis …

Presence Of Electron Donor/Acceptor Radiographic Contrast Media In Unusual Photosynthesis Environment Of Fresh Plant Cells: Near-Infrared And X-Ray Characterization, Tetiana Soloviova, Subhendra Sarkar, Amina Shahbaz, Aldona Gjoni

Publications and Research

Photosynthesis is a chemical process through which light energy is used to convert inorganic material (water and carbon dioxide) into organic molecules. Anaerobic photosynthesis, also known as anoxygenic photosynthesis, is the process by which certain bacteria use light energy to create organic compounds but do not adequately involve oxygen. In this experiment we are trying to influence photosynthesis (light and dark reactions: PS-I and PS-II by electron rich gadolinium/iodine complexes like Eovist and Isovue. We also performed X-ray and NIR reflection spectroscopy (NIRS) to measure Gd difusivity and PS-I/II infrared response. The results for X-ray (45kvp and 5 Mas ) …

Estimating Population Immunity Without Serological Testing, Andrew Lesniewski

Publications and Research

We propose an approximate methodology for estimating the overall level of immunity against COVID-19 in a population that has been affected by the recent epidemic. The methodology relies on the currently available mortality data and utilizes the properties of the SIR model. We illustrate the application of the method by estimating the recent levels of immunity in 10 US states with highest case numbers of COVID-19.

Impact Of Meteorological Factors On The Covid-19 Transmission: A Multicity Study In China, Jiangtao Liu, Ji Zhou, Jinxi Yao, Xiuxia Zhang, Lanyu Li, Xiaocheng Xu, Xiaotao He, Bo Wang, Shihua Fu, Tingting Niu, Jun Yan, Yanjun Shi, Xiaowei Ren, Jingping Niu, Weihao Zhu, Sheng Li, Bin Luo, Kai Zhang

Publications and Research

The purpose of the present study is to explore the associations between novel coronavirus disease 2019 (COVID- 19) case counts and meteorological factors in 30 provincial capital cities of China. We compiled a daily dataset including confirmed case counts, ambient temperature (AT), diurnal temperature range (DTR), absolute humidity (AH) and migration scale index (MSI) for each city during the period of January 20th to March 2nd, 2020. First, we explored the associations between COVID-19 confirmed case counts, meteorological factors, and MSI using non-linear regression. Then, we conducted a two-stage analysis for 17 cities with more than 50 confirmed cases. In …

Artificial Intelligence: A New Paradigm In Obstetrics And Gynecology Research And Clinical Practice, Pulwasha Iftikhar, Marcela V. Kuijpers, Azadeh Khayyat, Aqsa Iftikhar, Maribel Degouvia De Sa

Publications and Research

Artificial intelligence (AI) is growing exponentially in various fields, including medicine. This paper reviews the pertinent aspects of AI in obstetrics and gynecology (OB/GYN) and how these can be applied to improve patient outcomes and reduce the healthcare costs and workload for clinicians.

Herein, we will address current AI uses in OB/GYN, and the use of AI as a tool to interpret fetal heart rate (FHR) and cardiotocography (CTG) to aid in the detection of preterm labor, pregnancy complications, and review discrepancies in its interpretation between clinicians to reduce maternal and infant morbidity and mortality. AI systems can be used …

Proceedings Of The Cuny Games Conference 6.0, Robert O. Duncan, Joseph Bisz, Christina Boyle, Kathleen Offenholley, Maura A. Smale, Carolyn Stallard, Deborah Sturm

Publications and Research

The CUNY Games Network is an organization dedicated to encouraging research, scholarship and teaching in the developing field of games-based learning. We connect educators from every campus and discipline at CUNY and beyond who are interested in digital and non-digital games, simulations, and other forms of interactive teaching and inquiry-based learning. These proceedings summarize the CUNY Games Conference 6.0, where scholars shared research findings at a three-day event to promote and discuss game-based pedagogy in higher education. Presenters could share findings in oral presentations, posters, demos, or play testing sessions. The conference also included workshops on how to modify existing …

Polymers For Extrusion‐Based 3d Printing Of Pharmaceuticals: A Holistic Materials–Process Perspective, Mohammad A. Azad, Deborah Olawuni, Georgia Kimbell, Abu Zayed Badruddoza, Md. Shahadat Hossain, Tasnim Sultana

Publications and Research

Three dimensional (3D) printing as an advanced manufacturing technology is progressing to be established in the pharmaceutical industry to overcome the traditional manufacturing regime of ʹone size fits for allʹ. Using 3D printing, it is possible to design and develop complex dosage forms that can be suitable for tuning drug release. Polymers are the key materials that are necessary for 3D printing. Among all 3D printing processes, extrusion‐based (both fused deposition modeling (FDM) and pressure‐assisted microsyringe (PAM)) 3D printing is well researched for pharmaceutical manufacturing. It is important to understand which polymers are suitable for extrusion‐based 3D printing of pharmaceuticals …

From The Human To The Planetary: Speculative Futures Of Care, Miriam Ticktin

Publications and Research

This is largely a theoretical, speculative essay that takes on the question of what ‘care’ looks like at a moment when climate change is increasingly taking center stage in public and political discussions. Starting with two new practices, namely, humanitarian care for nonhumans and One Health collaborations, I seek to determine what forms of political care can incorporate the well-being of future generations and future iterations of the earth. After an exploration of One Health as an approach to planetary care, I ask what its parts enable us to think, despite its limitations; I focus on the new human-nonhuman assemblages …

Sickle Cell Disease Complications: Prevalence And Resource Utilization, Nirmish Shah, Menaka Bhor, Lin Xi, Jincy Paulose, Huseyin Yuce

Publications and Research

Objectives: This study evaluated the prevalence rate of vaso-occlusive crisis (VOC) episodes, rates of uncomplicated and complicated VOC episodes, and the primary reasons for emergency room (ER) visits and inpatient admissions for sickle cell disease (SCD) patients.

Methods: The Medicaid Analytic extracts database was used to identify adult SCD patients using claims from 01JUL2009-31DEC2012. The date of the first observed SCD claim was designated as the index date. Patients were required to have continuous medical and pharmacy benefits for .6 months baseline and .12 months follow-up period. Patient demographics, baseline clinical characteristics, the rate of uncomplicated and complicated VOC (VOC …

Comparative Clinical Outcomes Between Direct Oral Anticoagulants And Warfarin Among Elderly Patients With Non-Valvular Atrial Fibrillation In The Cms Medicare Population, Alpesh Amin, Oluwaseyi Dina, Allison Keshishian, Amol Dhamane, Anagha Nadkarni, Eric Carda, Cristina Russ, Lisa Rosenblatt, Jack Mardekian, Huseyin Yuce, Christine L. Baker

Publications and Research

Atrial fibrillation (AF) prevalence increases with age; > 80% of US adults with AF are aged ≥ 65 years. Compare the risk of stroke/systemic embolism (SE), major bleeding (MB), net clinical outcome (NCO), and major adverse cardiac events (MACE) among elderly non-valvular AF (NVAF) Medicare patients prescribed direct oral anticoagulants (DOACs) vs warfarin. NVAF patients aged ≥ 65 years who initiated DOACs (apixaban, dabigatran, and rivaroxaban) or warfarin were selected from 01JAN2013-31DEC2015 in CMS Medicare data. Propensity score matching was used to balance DOAC and warfarin cohorts. Cox proportional hazards models estimated the risk of stroke/SE, MB, NCO, and MACE. 37,525 …