Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 38,881 to 38,890 of 223,469 articles

Overall risk of cancer incidence attributable to adult body CT examinations: impact of a seven-year continuous quality improvement program.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
OBJECTIVES: To estimate the impact of a continuous dose reduction and quality improvement program on radiation-induced cancer risk in adult computed tomography (CT). METHODS: Between 2016 and 2022, the retrospective cohort study involved four phases:... read more 

Genome-wide detection of human 5' UTR variants that impact protein translation.

American journal of human genetics
The 5' untranslated region (5' UTR) of messenger RNAs (mRNAs) plays a central role in regulating protein synthesis initiation, particularly through the Kozak sequence and upstream open reading frames (uORFs). Genetic variants within these regulatory ... read more 

Integrated Implementation Strategies to Promote the Use of AI-Assisted Diagnostic Software for Lung Nodule Screening in China: Process Evaluation Based on the RE-AIM Framework.

JMIR formative research
BACKGROUND: While artificial intelligence (AI)-assisted diagnostic software holds promise for improving diagnostic efficiency and reducing disparities in health care delivery, its effective implementation in lower-tier health care settings remains li... read more 

Understanding User Intent in Code-Mixed Sexual and Reproductive Health Queries in Urban India: Hierarchical Classification Approach Using Large Language Models.

Journal of medical Internet research
BACKGROUND: Sexual and reproductive health (SRH) remains a stigmatized and taboo topic globally, limiting access to reliable information. These challenges are heightened in the Global South, where linguistic and cultural diversity further complicates... read more 

Performance of predictive AI-based clinical decision support systems across clinical domains: A systematic review and meta-analysis.

PLOS digital health
Despite advances in deep learning and transformer architectures, prior reviews have focused narrowly on traditional clinical decision support systems (CDSS) or single medical domains, leaving significant gaps in understanding contemporary AI-driven p... read more 

Improving the composition of donor milk using machine learning and optimisation techniques.

PloS one
BACKGROUND AND AIMS: The macronutrient composition of donor human milk (DHM) can vary substantially due to several factors such as maternal age, diet, and lactation duration. However, consistent macronutrient levels in DHM facilitate the administrati... read more 

Nickel price forecasting based onempirical mode decomposition and deep learning model with expansion mechanism.

PloS one
As a critical material for stainless steel production, electric vehicle (EV) batteries, and advanced technology alloys, nickel plays a pivotal role in the global energy transition, with its strategic value becoming increasingly evident. This study pr... read more 

An integrated model of financial socialization, technology, and financial capability in predicting financial well-being.

PloS one
This study develops and empirically tests an integrated framework that explains how financial socialisation, technological factors, and financial capability jointly shape financial behaviour and in an emerging economy context. Using data from 306 Vie... read more 

Wild mushroom consumption susceptibility among Chinese university students: A machine learning study.

PloS one
OBJECTIVES: To investigate factors associated with susceptibility to wild mushroom consumption using machine learning approaches and identify key predictors for targeted intervention development. METHODS: A cross-sectional survey of 216 Chinese unive... read more 

PepLM-GNN: A graph neural network framework leveraging pre-trained language models for peptide-protein binding prediction.

PLoS computational biology
MOTIVATION: The precise prediction of peptide-protein interaction (PepPI) is a core support for promoting breakthroughs in peptide drug research, as well as understanding the regulatory mechanisms of biomolecules. Researchers have developed several c... read more