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Exploring the Effect of an 8-Week AI-Composed Exercise Program on Pain Intensity and Well-Being in Patients With Spinal Pain: Retrospective Cohort Analysis.

JMIR formative research
BACKGROUND: Spinal pain, one of the most common musculoskeletal disorders (MSDs), significantly impacts the quality of life due to chronic pain and disability. Physical activity has shown promise in managing spinal pain, although optimizing adherence...

Impact of pectoral muscle removal on deep-learning-based breast cancer risk prediction.

Physics in medicine and biology
State-of-the-art breast cancer risk (BCR) prediction models have been originally trained on mammograms with pectoral muscle (PM) included. This study investigated whether excluding PM during training/fine-tuning improves the model's BCR discriminatio...

[Validation of a decision tree for selective dry cow therapy of dairy for a digital expert system].

Tierarztliche Praxis. Ausgabe G, Grosstiere/Nutztiere
In this study, a decision tree derived from scientific literature on selective dry cow therapy (ST), which was developed as a knowledge base for a digital expert system, was evaluated. The decision tree merges algorithmic (based on cell count results...

Prognosis of p16 and Human Papillomavirus Discordant Oropharyngeal Cancers and the Exploration of Using Natural Language Processing to Analyze Free-Text Pathology Reports.

JCO clinical cancer informatics
PURPOSE: Treatment deintensification for human papillomavirus-positive (HPV+)-associated oropharyngeal cancer (OPC) has been the catalyst of experts worldwide. In situ hybridization is optimal to identify HPV+ OPC, but immunohistochemistry for its su...

Multi-omics and single-cell analysis reveals machine learning-based pyrimidine metabolism-related signature in the prognosis of patients with lung adenocarcinoma.

International journal of medical sciences
Pyrimidine metabolism is a hallmark of tumor metabolic reprogramming, while its significance in the prognostic and therapeutic implications of patients with lung adenocarcinoma (LUAD) still remains unclear. In this study, an integrated framework of...

Leveraging natural language processing for efficient information extraction from breast cancer pathology reports: Single-institution study.

PloS one
BACKGROUND: Pathology reports provide important information for accurate diagnosis of cancer and optimal treatment decision making. In particular, breast cancer has known to be the most common cancer in women worldwide.

Development and validation of interpretable machine learning models for triage patients admitted to the intensive care unit.

PloS one
OBJECTIVES: Developing and validating interpretable machine learning (ML) models for predicting whether triaged patients need to be admitted to the intensive care unit (ICU).

Application of Artificial Intelligence Software to Identify Emotions of Lung Cancer Patients in Preoperative Health Education: A Cross-Sectional Study.

Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
AIM(S): To determine the correlation between preoperative health education and the emotions of lung cancer patients, artificial intelligence software was used.

A multimodal machine learning algorithm improved diagnostic accuracy for otitis media in a school aged Aboriginal population.

Journal of biomedical informatics
OBJECTIVE: Otitis Media (OM) - ear infection - can lead to hearing loss and associated developmental delay. There are several subgroups of OM which can be difficult to diagnose accurately, even for experienced clinicians. AI and machine learning algo...

Recurrence patterns and prediction of survival after recurrence for gallbladder cancer.

Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
BACKGROUND: Gallbladder cancer (GBC) is associated with a poor prognosis. Recurrence patterns and their effect on survival remain ill-defined. This study aimed to analyze recurrence patterns and develop a machine learning (ML) model to predict surviv...