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From the -Factor to Cognitive Content: Detection and Discrimination of Psychopathologies Based on Explainable Artificial Intelligence.

Depression and anxiety
Differentiating psychopathologies is challenging due to shared underlying mechanisms, such as the -factor. Nevertheless, recent methodological advances suggest that distinct linguistic markers can help detect and differentiate these conditions. This...

Effect of artificial intelligence driven therapeutic lifestyle changes (AI-TLC) intervention on health behavior and health among obesity pregnant women in China: a randomized controlled trial protocol.

Frontiers in public health
INTRODUCTION: Obesity has reached epidemic proportions globally, posing significant challenges to public health and economic stability. In China, the prevalence of obesity is increasing rapidly, particularly among pregnant women, who face unique risk...

Predicting central lymph node metastasis in papillary thyroid microcarcinoma: a breakthrough with interpretable machine learning.

Frontiers in endocrinology
OBJECTIVE: To develop and validate an interpretable machine learning (ML) model for the preoperative prediction of central lymph node metastasis (CLNM) in papillary thyroid microcarcinoma (PTMC).

Exploring the effect of the triglyceride-glucose index on bone metabolism in prepubertal children, a retrospective study: insights from traditional methods and machine-learning-based bone remodeling prediction.

PeerJ
BACKGROUND: Childhood obesity poses a significant risk to bone health, but the impact of insulin resistance (IR) on bone metabolism in prepubertal children, as assessed by the triglyceride-glucose (TyG) index, remains underexplored. Bone turnover mar...

Interpretable noninvasive diagnosis of tuberculous pleural effusion using LGBM and SHAP: development and clinical application of a machine learning model.

PeerJ
BACKGROUND: Tuberculous pleural effusion (TPE) is a prevalent tuberculosis complication, with diagnosis presenting considerable challenges. Timely and precise identification of TPE is vital for effective patient management and prognosis, yet existing...

Shaping the future of medical education: A cross-sectional study on ChatGPT attitude and usage among medical students in Sudan.

PloS one
BACKGROUND: Artificial intelligence (AI) is revolutionizing education globally, yet its adoption in medical education remains inadequately understood. ChatGPT, a generative AI tool, offers promising yet doubtful potential for enhancing academic and c...

Convolutional neural network using magnetic resonance brain imaging to predict outcome from tuberculosis meningitis.

PloS one
INTRODUCTION: Tuberculous meningitis (TBM) leads to high mortality, especially amongst individuals with HIV. Predicting the incidence of disease-related complications is challenging, for which purpose the value of brain magnetic resonance imaging (MR...

Leveraging transformers and explainable AI for Alzheimer's disease interpretability.

PloS one
Alzheimer's disease (AD) is a progressive brain ailment that causes memory loss, cognitive decline, and behavioral changes. It is quite concerning that one in nine adults over the age of 65 have AD. Currently there is almost no cure for AD except ver...

Personalized treatment decision-making using a machine learning-derived lactylation signature for breast cancer prognosis.

Frontiers in immunology
BACKGROUND: Breast cancer is a heterogeneous malignancy with complex molecular characteristics, making accurate prognostication and treatment stratification particularly challenging. Emerging evidence suggests that lactylation, a novel post-translati...

Artificial intelligence and omics-based autoantibody profiling in dementia.

Frontiers in immunology
INTRODUCTION: Dementia is a neurodegenerative syndrome marked by the accumulation of disease-specific proteins and immune dysregulation, including autoimmune mechanisms involving autoantibodies. Current diagnostic methods are often invasive, time-con...