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Machine learning for precision medicine

Sarah J. MacEachern, Nils D. Forkert • Genome (2020)

Precision medicine is an emerging approach to clinical research and patient care that focuses on understanding and treating disease by integrating multi-modal or multi-omics data from an individual to make patient-tailored decisions. With t...

OPENALEX Open Access DOI: https://doi.org/10.1139/gen-2020-0131

Comparing Clinical Metadata Fusion Strategies for Diabetic and Hypertensive Retinopathy Classification

Vinicius de Carvalho Rispoli, Alan Müller, Weverson Garcia Medeiros, Marília Miranda Forte Gomes et al. • Machine Learning and Knowledge Extraction (2026)

Structured clinical variables may complement fundus photographs, but the most appropriate point at which to integrate them into a retinal foundation model remains uncertain. This study compares an image-only baseline with three strategies f...

DOAJ Open Access (DOAJ) DOI: 10.3390/make8100299

Discovering subtypes with imaging signatures in the Motoric Cognitive Risk Syndrome Consortium using weakly supervised clustering

Bhargav Teja Nallapu, Ali Ezzati, Helena M. Blumen, Kellen K. Petersen et al. • Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring (2025)

ABSTRACT INTRODUCTION Understanding the heterogeneity of brain structure in individuals with the Motoric Cognitive Risk Syndrome (MCR) may improve the current risk assessments of dementia. METHODS We used data from six cohorts from the MCR ...

DOAJ Open Access (DOAJ) DOI: 10.1002/dad2.70197

Taxonomy-based data representation for data mining: an example of the magnitude of risk associated with H. pylori infection

Inese Polaka, Danute Razuka-Ebela, Jin Young Park, Marcis Leja • BioData Mining (2021)

Abstract Background The amount of available and potentially significant data describing study subjects is ever growing with the introduction and integration of different registries and data banks. The single specific attribute of these data...

DOAJ Open Access (DOAJ) DOI: 10.1186/s13040-021-00271-w

Identification of arachidonic acid metabolism-related diagnostic markers in heart failure based on bioinformatics analysis and machine learning

Saiqing Chen, Chunxia Zhang, Yueting Yu • Frontiers in Cardiovascular Medicine (2025)

BackgroundHeart failure (HF) represents the terminal phase of multiple cardiovascular conditions and is associated with significant morbidity and mortality rates. Arachidonic acid (AA), an essential fatty acid, plays a crucial role in modul...

DOAJ Open Access (DOAJ) DOI: 10.3389/fcvm.2025.1625064

Machine learning-based diagnostic prediction of minimal change disease: model development study

Ryunosuke Noda, Daisuke Ichikawa, Yugo Shibagaki • Scientific Reports (2024)

Abstract Minimal change disease (MCD) is a common cause of nephrotic syndrome. Due to its rapid progression, early detection is essential; however, definitive diagnosis requires invasive kidney biopsy. This study aims to develop non-invasiv...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-024-73898-4

Resistance to Medical Artificial Intelligence

Chiara Longoni, Andrea Bonezzi, Carey K. Morewedge • Journal of Consumer Research (2019)

Abstract Artificial intelligence (AI) is revolutionizing healthcare, but little is known about consumer receptivity to AI in medicine. Consumers are reluctant to utilize healthcare provided by AI in real and hypothetical choices, separate a...

OPENALEX Open Access DOI: https://doi.org/10.1093/jcr/ucz013

Artificial intelligence model to predict pregnancy and multiple pregnancy risk following in vitro fertilization-embryo transfer (IVF-ET)

Jen-Yu Wen, Chung-Fen Liu, Ming-Ting Chung, Yung-Chieh Tsai • Taiwanese Journal of Obstetrics & Gynecology (2022)

Objective: To decrease multiple pregnancy risk and sustain optimal pregnancy chance by choosing suitable number of embryos during transfer, this study aims to construct artificial intelligence models to predict the pregnancy outcome and mul...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.tjog.2021.11.038

PERMEPSY: a multicentre, randomized, double-blind proof-of-concept trial of personalized metacognitive training for adults with psychosis — a study protocol

Maria Lamarca, Maria Lamarca, Maria Lamarca, Maria Lamarca et al. • Frontiers in Psychiatry (2026)

BackgroundWhile psychological interventions are effective at improving symptoms of psychosis, accessible, cost- and time-efficient treatments remain limited. Personalized medicine has emerged as a promising approach, tailoring interventions...

DOAJ Open Access (DOAJ) DOI: 10.3389/fpsyt.2026.1711659

Saikosaponin b1 Attenuates Liver Fibrosis by Blocking STAT3/Gli1 Interaction and Inducing Gli1 Degradation

Meiyu Shao, Xiaoqing Zhang, Jiamei Sun, Hongyan Dong et al. • Exploration (2025)

ABSTRACT Saikosaponin b1 (Ssb1), a natural oleanane‐type triterpenoid saponin, exhibits antifibrosis activity by inhibiting the activation of hepatic stellate cells (HSCs), but the specific underlying molecular mechanisms are unknown. Here,...

DOAJ Open Access (DOAJ) DOI: 10.1002/EXP.70000

Introducing Artificial Intelligence Training in Medical Education

Ketan Paranjape, Michiel Schinkel, Rishi S. Nannan Panday, Josip Car et al. • JMIR Medical Education (2019)

Health care is evolving and with it the need to reform medical education. As the practice of medicine enters the age of artificial intelligence (AI), the use of data to improve clinical decision making will grow, pushing the need for skillf...

OPENALEX cc-by DOI: https://doi.org/10.2196/16048 PMC: 6918207