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Data-driven identification of subgroups in early rheumatoid arthritis: mortality and cardiovascular disease in a cohort from western Norway.

RMD open
AIM: To identify subgroups of early rheumatoid arthritis (RA) based on comorbidities and RA manifestations and to investigate their associated risks of cardiovascular events and mortality.

Prediction of long-term uncorrected distance visual acuity in surgically SMILE corrected myopic eyes using machine learning.

BMJ open ophthalmology
BACKGROUND: This study aimed to create machine learning (ML) models to predict the long-term uncorrected distance visual acuity (UDVA) in myopic eyes corrected by small incision lenticule extraction (SMILE).

Exploring Young Adults' Attitudes Toward AI-Driven mHealth Apps: Qualitative Study.

JMIR human factors
BACKGROUND: Artificial intelligence (AI)-driven mobile health (mHealth) apps are emerging as a promising tool for health management, yet little is known about users' psychological perceptions and attitudes toward these technologies. Understanding the...

Preferences of Patients With Tuberculosis for AI-Assisted Remote Health Management: Discrete Choice Experiment.

Journal of medical Internet research
BACKGROUND: Tuberculosis remains a major global public health challenge, especially in low-resource settings where long-term treatment adherence and regular follow-up are critical. The integration of artificial intelligence (AI) into remote health ma...

Multi-omics based consensus subtypes, development of prognostic signature, and identification of INHBB as a potential therapeutic target in colorectal cancer.

Functional & integrative genomics
This study aims to refine molecular subtypes via multi-omics data, develop a prognostic signature, and identify novel biomarkers in colorectal cancer (CRC). On the basis of the multi-omics data, the MOVICS R package was used to divide patients with C...

Development and validation of machine-learning model based on dynamic tumor markers in predicting pathological complete response after neoadjuvant chemoradiotherapy in patients with locally advanced rectal cancer: a multicenter cohort study.

International journal of colorectal disease
OBJECTIVE: In this study, we constructed a new pCR predictor based on dynamic tumor marker changes before and after NCRT, the dynamic tumor marker score (DTMS), and combined it with other clinicopathological features to build a machine-learning model...

Construction of a predictive model for the risk of moderate-to-severe cancer-related fatigue in colorectal cancer chemotherapy patients: an interpretable machine learning approach.

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
PURPOSE: This study aimed to analyze the influencing factors of moderate-to-severe cancer-related fatigue (CRF) in colorectal cancer (CRC) chemotherapy patients and to develop a predictive risk stratification model.

The Cost-Effectiveness of AI-Assisted Colonoscopy as a Primary or Secondary Screening Test in a Population-Based Colorectal Cancer Screening Program: Markov Modeling-Based Cost Effectiveness Analysis.

Journal of medical Internet research
BACKGROUND: Colorectal cancer (CRC) is the third most common cancer worldwide and poses a heavy burden on health care systems. Early screening for CRC through colonoscopy can effectively reduce both the incidence and mortality associated with CRC. Ho...

From zero- to few-shot: deep temporal learning of wrist EMG enables scalable cross-user gesture recognition.

Journal of neural engineering
Wrist electromyography (EMG) is emerging as an enticing wearable input modality for human-machine interaction. Traditionally recorded from the forearm for use in transradial prostheses, wrist-based EMG sensors are now being integrated into devices su...

Machine learning based classification of imagined speech electroencephalogram data from the amplitude and phase spectrum of frequency domain EEG signal.

Biomedical physics & engineering express
Imagined speech classification involves decoding brain signals to recognize verbalized thoughts or intentions without actual speech production. This technology has significant implications for individuals with speech impairments, offering a means to ...