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Construction of a prognostic model for endometrial cancer related to programmed cell death using WGCNA and machine learning algorithms.

Frontiers in immunology
BACKGROUND: Programmed cell death (PCD) refers to a regulated and active process of cellular demise, initiated by specific biological signals. PCD plays a crucial role in the development, progression, and drug resistance of uterine corpus endometrial...

Clustering and classification of early knee osteoarthritis using machine-learning analysis of step-up and down test kinematics in recreational table tennis players.

PeerJ
OBJECTIVE: Early detection of knee osteoarthritis is crucial for improving patient outcomes. While conventional imaging methods often fail to detect early changes and require specialized expertise for interpretation, this study aimed to investigate t...

Acceptance of Using Artificial Intelligence and Digital Technology for Mental Health Interventions: The Development and Initial Validation of the UTAUT-AI-DMHI.

Clinical psychology & psychotherapy
Digital health technologies are being increasingly integrated into mental healthcare. This means that patients have different treatment options, and clinicians need to consider different ways of supporting their patients too. The adoption of Digital ...

How should artificial intelligence be used in breast screening? Women's reasoning about workflow options.

PloS one
Studies show that breast screening participants are open to artificial intelligence (AI) in breast screening, but hold concerns about AI performance, governance, equitable access, and dependence on technology. Little is known of consumers' views on h...

Preoperative kidney tumor risk estimation with AI: From logistic regression to transformer.

PloS one
We consider the problem of renal mass risk classification to support doctors in adjuvant treatment decisions following nephrectomy. Recommendation of adjuvant therapy based on the mass appearance poses two major challenges: first, morphologic pattern...

Deep learning reconstruction of free-breathing, diffusion-weighted imaging of the liver: A comparison with conventional free-breathing acquisition.

PloS one
This study aimed to compare image quality and solid focal liver lesion (FLL) assessments between free-breathing, diffusion-weighted imaging using deep learning reconstruction (FB-DL-DWI) and conventional DWI (FB-C-DWI) in patients undergoing clinical...

Urban-rural disparities in fall risk among older Chinese adults: insights from machine learning-based predictive models.

Frontiers in public health
BACKGROUND: Falls among older adults are a significant challenge to global healthy aging. Identifying key factors and differences in fall risks, along with developing predictive models, is essential for differentiated and precise interventions in Chi...

Unveiling sub-populations in critical care settings: a real-world data approach in COVID-19.

Frontiers in public health
BACKGROUND: Disease presentation and progression can vary greatly in heterogeneous diseases, such as COVID-19, with variability in patient outcomes, even within the hospital setting. This variability underscores the need for tailored treatment approa...

Comparative evaluation of the accuracy and reliability of ChatGPT versions in providing information on infection.

Frontiers in public health
OBJECTIVE: This study aimed to evaluate the accuracy and reliability of responses provided by three versions of ChatGPT (ChatGPT-3.5, ChatGPT-4, and ChatGPT-4o) to questions related to (Hp) infection, as well as to explore their potential applicatio...

Acoustic-based machine learning approaches for depression detection in Chinese university students.

Frontiers in public health
BACKGROUND: Depression is major global public health problems among university students. Currently, the evaluation and monitoring of depression predominantly depend on subjective and self-reported methods. There is an urgent necessity to develop obje...