AI Medical Compendium Topic

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Can off-the-shelf visual large language models detect and diagnose ocular diseases from retinal photographs?

BMJ open ophthalmology
BACKGROUND: The advent of generative artificial intelligence has led to the emergence of multiple vision large language models (VLLMs). This study aimed to evaluate the capabilities of commonly available VLLMs, such as OpenAI's GPT-4V and Google's Ge...

Credit and blame for AI-generated content: Effects of personalization in four countries.

Annals of the New York Academy of Sciences
Generative artificial intelligence (AI) raises ethical questions concerning moral and legal responsibility-specifically, the attributions of credit and blame for AI-generated content. For example, if a human invests minimal skill or effort to produce...

Using Machine Learning Models to Predict Pathologic Complete Response to Neoadjuvant Chemotherapy in Breast Cancer.

JCO clinical cancer informatics
PURPOSE: Neoadjuvant chemotherapy (NAC) is increasingly used in breast cancer. Predictive modeling is useful in predicting pathologic complete response (pCR) to NAC. We test machine learning (ML) models to predict pCR in breast cancer and explore met...

Cohort profile: AI-driven national Platform for CCTA for clinicaL and industriaL applicatiOns (APOLLO).

BMJ open
PURPOSE: Coronary CT angiography (CCTA) is well established for the diagnostic evaluation and prognostication of coronary artery disease (CAD). The growing burden of CAD in Asia and the emergence of novel CT-based risk markers highlight the need for ...

Enhancing Small-for-Gestational-Age Prediction: Multi-Country Validation of Nuchal Thickness, Estimated Fetal Weight, and Machine Learning Models.

Prenatal diagnosis
OBJECTIVE: The first objective is to develop a nuchal thickness reference chart. The second objective is to compare rule-based algorithms and machine learning models in predicting small-for-gestational-age infants.

Early detection of disease outbreaks and non-outbreaks using incidence data: A framework using feature-based time series classification and machine learning.

PLoS computational biology
Forecasting the occurrence and absence of novel disease outbreaks is essential for disease management, yet existing methods are often context-specific, require a long preparation time, and non-outbreak prediction remains understudied. To address this...

Using ChatGPT for medical education: the technical perspective.

BMC medical education
BACKGROUND: The chatbot application Bennie and the Chats was introduced due to the outbreak of COVID-19, which is aimed to provide substitution for teaching conventional clinical history-taking skills. It was implemented with DialogFlow with preset r...

A deep-learning retinal aging biomarker for cognitive decline and incident dementia.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: The utility of retinal photography-derived aging biomarkers for predicting cognitive decline remains under-explored.

Machine learning to risk stratify chest pain patients with non-diagnostic electrocardiogram in an Asian emergency department.

Annals of the Academy of Medicine, Singapore
INTRODUCTION: Elevated troponin, while essential for diagnosing myocardial infarction, can also be present in non-myocardial infarction conditions. The myocardial-ischaemic-injury-index (MI3) algorithm is a machine learning algorithm that considers a...