William B. Weeks
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View article: Association Between Average Annual US Medical Specialty Compensation and Percentage of Trainees in the Specialty Who Are Female
Association Between Average Annual US Medical Specialty Compensation and Percentage of Trainees in the Specialty Who Are Female Open
Background Female physicians have lower incomes than male physicians. While overall sex-based income disparities are dramatic, compensation differs considerably across specialties. A better understanding of the relationship between anticip…
View article: Benchmarking robustness of automated CT pancreas segmentation: achieving human-level reliability through human-in-the-loop optimization
Benchmarking robustness of automated CT pancreas segmentation: achieving human-level reliability through human-in-the-loop optimization Open
Background Deep learning–based pancreas segmentation in CT has advanced rapidly yet remains evaluated primarily with mean overlap metrics that fail to capture robustness—defined as the proportion of cases reaching human-level performance. …
View article: Leveraging Large Language Models to Generate Multiple-Choice Questions for Ophthalmology Education
Leveraging Large Language Models to Generate Multiple-Choice Questions for Ophthalmology Education Open
Importance Multiple choice questions (MCQs) are an important and integral component of ophthalmology residency training evaluation and board certification; however, high-quality questions are difficult and time-consuming to draft. Objectiv…
View article: Bridging gaps in ophthalmology education through large language models
Bridging gaps in ophthalmology education through large language models Open
Purpose: To assess the performance of general-domain large language models (LLMs), particularly OpenAI’s Generative Pre-trained Transformer (GPT) models, within the American Academy of Ophthalmology (AAO) Self-Assessment Program, which is …
View article: Liver MRI proton density fat fraction inference from contrast enhanced CT images using deep learning: A proof-of-concept study
Liver MRI proton density fat fraction inference from contrast enhanced CT images using deep learning: A proof-of-concept study Open
Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common cause of chronic liver disease worldwide, affecting over 30% of the global general population. Its progressive nature and association with other chronic di…
View article: Towards reliable use of artificial intelligence to classify otitis media using otoscopic images: Addressing bias and improving data quality
Towards reliable use of artificial intelligence to classify otitis media using otoscopic images: Addressing bias and improving data quality Open
Ear disease contributes significantly to global hearing loss, with recurrent otitis media being a primary preventable cause in children, impacting development. Artificial intelligence (AI) offers promise for early diagnosis via otoscopic i…
View article: Cancer Detection in Breast MRI Screening via Explainable AI Anomaly Detection
Cancer Detection in Breast MRI Screening via Explainable AI Anomaly Detection Open
An anomaly detection model for breast cancer on MRI scans achieved high performance, surpassing binary classification in high- and low-cancer-prevalence scenarios and producing explanation heat maps not significantly different from radiolo…
View article: Modeling protective meningococcal antibody responses and factors influencing antibody persistence following vaccination with MenAfriVac using machine learning
Modeling protective meningococcal antibody responses and factors influencing antibody persistence following vaccination with MenAfriVac using machine learning Open
Meningococcal meningitis poses a significant public health burden in the meningitis belt region of sub-Saharan Africa. The introduction of the meningococcal PsA-TT vaccine (MenAfriVac®) has successfully eliminated Neisseria meningitidis se…
View article: Computer-Aided Detection (CADe) of Small Metastatic Prostate Cancer Lesions on 3D PSMA PET Volumes Using Multi-Angle Maximum Intensity Projections
Computer-Aided Detection (CADe) of Small Metastatic Prostate Cancer Lesions on 3D PSMA PET Volumes Using Multi-Angle Maximum Intensity Projections Open
Objectives: We aimed to develop and evaluate a novel computer-aided detection (CADe) approach for identifying small metastatic biochemically recurrent (BCR) prostate cancer (PCa) lesions on PSMA-PET images, utilizing multi-angle Maximum In…
View article: COVID-19 Pandemic-Era Changes in Sudden Unexpected Infant Death in the United States
COVID-19 Pandemic-Era Changes in Sudden Unexpected Infant Death in the United States Open
OBJECTIVE We aimed to investigate COVID-19 pandemic-era changes in postperinatal sudden unexpected infant death (SUID) and their association with maternal sociodemographic factors. METHODS We conducted a nationwide cohort study using Cente…
View article: AI-Enabled Screening for Retinopathy of Prematurity in Low-Resource Settings
AI-Enabled Screening for Retinopathy of Prematurity in Low-Resource Settings Open
Importance Retinopathy of prematurity (ROP) is the leading cause of preventable childhood blindness worldwide. If detected and treated early, ROP-associated blindness is preventable; however, identifying patients who might respond to treat…
View article: Influence of High-Performance Image-to-Image Translation Networks on Clinical Visual Assessment and Outcome Prediction: Utilizing Ultrasound to MRI Translation in Prostate Cancer
Influence of High-Performance Image-to-Image Translation Networks on Clinical Visual Assessment and Outcome Prediction: Utilizing Ultrasound to MRI Translation in Prostate Cancer Open
Purpose: This study examines the core traits of image-to-image translation (I2I) networks, focusing on their effectiveness and adaptability in everyday clinical settings. Methods: We have analyzed data from 794 patients diagnosed with pros…
View article: Enhanced Macular Telangiectasia Type 2 Detection: Leveraging Self-Supervised Learning and Ensemble Models
Enhanced Macular Telangiectasia Type 2 Detection: Leveraging Self-Supervised Learning and Ensemble Models Open
Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
View article: Biological and Radiological Dictionary of Radiomics Features: Addressing Understandable AI Issues in Personalized Prostate Cancer; Dictionary Version PM1.0
Biological and Radiological Dictionary of Radiomics Features: Addressing Understandable AI Issues in Personalized Prostate Cancer; Dictionary Version PM1.0 Open
We investigate the connection between visual semantic features defined in PI-RADS and associated risk factors, moving beyond abnormal imaging findings, establishing a shared framework between medical and AI professionals by creating a stan…
View article: Performance of explainable artificial intelligence in guiding the management of patients with a pancreatic cyst
Performance of explainable artificial intelligence in guiding the management of patients with a pancreatic cyst Open
EBM models had greater sensitivity and specificity for identifying the correct management compared with either clinical management or previous AI models. The model predictions are demonstrated to be interpretable by clinicians.
View article: Machine learning to evaluate the relationship between social determinants and diabetes prevalence in New York City
Machine learning to evaluate the relationship between social determinants and diabetes prevalence in New York City Open
Introduction Diabetes is a leading contributor to cardiovascular disease and mortality; social determinants of health (SDOH) are associated with disparities in diabetes risk. Quantifying the cumulative impact of SDOH and identifying the SD…
View article: A Methodology for Using Large Language Models to Create User-Friendly Applications for Medicaid Redetermination and Other Social Services
A Methodology for Using Large Language Models to Create User-Friendly Applications for Medicaid Redetermination and Other Social Services Open
A Methodology for Using Large Language Models to Create User-Friendly Applications for Medicaid Redetermination and Other Social Services
View article: Maternal Obesity and Risk of Sudden Unexpected Infant Death
Maternal Obesity and Risk of Sudden Unexpected Infant Death Open
Importance Rates of maternal obesity are increasing in the US. Although obesity is a well-documented risk factor for numerous poor pregnancy outcomes, it is not currently a recognized risk factor for sudden unexpected infant death (SUID). …
View article: The Ecology of Economic Distress and Life Expectancy
The Ecology of Economic Distress and Life Expectancy Open
Objectives To determine whether life expectancy (LE) changes between 2000 and 2019 were associated with race, rural status, local economic prosperity, and changes in local economic prosperity, at the county level. Methods Between 12/1/22 a…
View article: Artificial intelligence: promise and peril in achieving the quadruple aim in healthcare
Artificial intelligence: promise and peril in achieving the quadruple aim in healthcare Open
OPINION article Front. Artif. Intell., 19 June 2024Sec. Medicine and Public Health Volume 7 - 2024 | https://doi.org/10.3389/frai.2024.1430756
View article: Storytelling in Scientific Conferences: Mitigating Misinformation Risk
Storytelling in Scientific Conferences: Mitigating Misinformation Risk Open
Keywords: misinformation, misinformation related to health, statistical analysis, COVID-19 vaccine, adverse drug reactions
View article: Do High-Performance Image-to-Image Translation Networks Enable the Discovery of Radiomic Features? Application to MRI Synthesis from Ultrasound in Prostate Cancer
Do High-Performance Image-to-Image Translation Networks Enable the Discovery of Radiomic Features? Application to MRI Synthesis from Ultrasound in Prostate Cancer Open
This study investigates the foundational characteristics of image-to-image translation networks, specifically examining their suitability and transferability within the context of routine clinical environments, despite achieving high level…
View article: Bridging the rural‐urban divide: An implementation plan for leveraging technology and artificial intelligence to improve health and economic outcomes in rural America
Bridging the rural‐urban divide: An implementation plan for leveraging technology and artificial intelligence to improve health and economic outcomes in rural America Open
Rural residents have higher age-adjusted mortality and prevalence rates for cardiovascular disease, diabetes, cancer, unintentional injury, and stroke.1-8 Those living in rural settings experience shorter lifespans9-11 amplified by higher …
View article: Health and Wealth in America
Health and Wealth in America Open
Citation: Weeks WB, Lavista Ferres JM and Weinstein JN (2024) Health and Wealth in America. Int J Public Health 69:1607224. doi: 10.3389/ijph.2024.1607224
View article: Self-Supervised Learning for Improved Optical Coherence Tomography Detection of Macular Telangiectasia Type 2
Self-Supervised Learning for Improved Optical Coherence Tomography Detection of Macular Telangiectasia Type 2 Open
Importance Deep learning image analysis often depends on large, labeled datasets, which are difficult to obtain for rare diseases. Objective To develop a self-supervised approach for automated classification of macular telangiectasia type …
View article: All Sustainable Development Goals Support Good Health and Well-Being
All Sustainable Development Goals Support Good Health and Well-Being Open
COMMENTARY Int J Public Health, 27 December 2023 https://doi.org/10.3389/ijph.2023.1606901
View article: Hospital use of common Z-codes for Medicare fee-for-service beneficiaries, 2017–2021
Hospital use of common Z-codes for Medicare fee-for-service beneficiaries, 2017–2021 Open
Recognizing the impact of the social determinants of health (SDOH) on health outcomes, in 2016, the Centers for Medicare and Medicaid Services recommended the use of International Classification of Diseases, 10th Revision (ICD-10), Z-codes…
View article: Comprehensive framework for evaluation of deep neural networks in detection and quantification of lymphoma from PET/CT images: clinical insights, pitfalls, and observer agreement analyses
Comprehensive framework for evaluation of deep neural networks in detection and quantification of lymphoma from PET/CT images: clinical insights, pitfalls, and observer agreement analyses Open
This study addresses critical gaps in automated lymphoma segmentation from PET/CT images, focusing on issues often overlooked in existing literature. While deep learning has been applied for lymphoma lesion segmentation, few studies incorp…