Latest AI and machine learning research in primary care for healthcare professionals.
We propose an experience-guided cascaded multi-agent framework for Breast Ultrasound Screening and Diagnosis, called BUSD-Agent, that aims to reduce diagnostic escalation and unnecessary biopsy referrals. Our framework models screening and diagnosis as a two-stage, selective decision-making process. A lightweight `screening clinic' agent, restricted to classification models as tools, selectively f...
Introduction: Cardiovascular diseases (CVDs) are the leading cause of death globally, with rising burdens in Africa due to ageing populations, lifestyle changes, and poor risk factor control. Conventional risk scores developed in high-income settings often perform poorly in African populations. Machine-learning (ML) approaches offer potential to improve prediction by capturing complex, non-linear ...
In recent years, high dimensional omics analyses have become more commonplace for investigating complex biological systems. Typically, these studies a...
Objectives: Artificial intelligence (AI) enabled digital stethoscopes combine phonocardiography and electrocardiography to support detection of cardia...
Early detection of myometrial invasion is critical for the staging and life-saving management of endometrial carcinoma (EC), a prevalent global malign...
Background: Advances in wearable devices and machine-learning-based ECG analysis enable highly accurate detection of atrial fibrillation (AF) outside ...
Non-alcoholic fatty liver disease (NAFLD) is a globally prevalent hepatic condition caused by the buildup of fat in the liver. It is frequently associ...
Abstract. Genetic diagnosis remains a formidable challenge characterized by a diagnostic odyssey that spans years, with over half of rare disease pati...
Neural organoids have revolutionized how human neurodevelopmental disorders (NDDs) are studied. Yet, their utility for screening chemical hazards and ...
Background: The ability of large language models (LLMs) to work collaboratively and screen studies in a systematic review (SR) is under-explored. Henc...
Background: Large language models (LLMs) show promise for clinical decision support, yet most validation studies evaluate single models, leaving quest...
Virtual screening aims to efficiently identify active ligands from massive chemical libraries for a given target pocket. Recent CLIP-style models such...
Background: Risk screening for pre-eclampsia relies on accurate gestational age assessment, but routine access to ultrasound-based gestational dating ...
ABSTRACT Objectives: To quantify patterns of preventable death in Australian coronial findings, measure government compliance with coroner recommendat...
Integrating the cellular resolution of single-cell RNA sequencing (scRNA-seq) with the phenotypic depth of population-scale biobanks is essential for ...
Widespread screening for Adolescent Idiopathic Scoliosis (AIS) is critical for timely intervention but is currently constrained by the radiation risks...
Body mass index (BMI), type 2 diabetes (T2D) and associated cardiometabolic features modify Alzheimer's disease (AD) risk, yet shared mechanisms remai...
Aging is asynchronous across cells and organs, but whether plasma proteins can capture cell type-specific aging and predict disease and mortality rema...
Identifying type 2 diabetes mellitus can be challenging, particularly for primary care physicians. Clinical decision support systems incorporating art...
Background: Natural language processing (NLP) systems integrated into clinical workflows show promise for detecting early cognitive impairment, yet ca...