Latest AI and machine learning research in alternative medicine for healthcare professionals.
A precise diagnosis and customized treatment become more difficult by the genomic heterogeneity of breast cancer (BRCA). In order to examine gene expression data from two separate Gene Expression Omnibus (GEO) microarray datasets, we used a integrative approach in this study that combined bioinformatics and machine learning. We were able to distinguish between universal and subtype-specific transc...
Accurate prediction of vehicle COâ‚‚ emissions is challenging due to heterogeneous engine characteristics, nonlinear interactions among fuel, mechanical, and operational parameters, and variable driving conditions. This study proposes a high-performance machine learning framework that combines multi-layer perceptron (MLP) architectures with nature-inspired metaheuristic optimization to model vehicle...
ETHNOPHARMACOLOGICAL RELEVANCE: Ulcerative colitis (UC) is a chronic inflammatory bowel disease characterized by symptoms such as persistent diarrhea....
Under the background of the rapid development of artificial intelligence (AI) technology, the postgraduate training of acupuncture professional master...
Colorectal cancer (CRC) is the third most common malignancy and the second leading cause of cancer-related death worldwide, yet current prognostic str...
Prostate cancer exhibits complex transcriptional heterogeneity that underlies disease progression and therapeutic resistance. We developed an integrat...
The cerebro-cerebellar system, a network of bidirectional loops between the cerebellum and cerebral cortex, is crucial for coordinating motor control,...
Artificial intelligence tools are increasingly being used to automate the evidence synthesis process, particularly for researcher-intensive tasks such...
BACKGROUND: Chronic low back pain (CLBP) is among the most disabling musculoskeletal disorders worldwide. Traditional in-person rehabilitation is ofte...
Pregnant women and children have been underrepresented in clinical studies due to ethical concerns and perceived vulnerabilities. This resulted in a s...
BACKGROUND: Esophageal squamous cell cancer (ESCC) is a malignancy derived from the Esophagus, and dysregulation of the cGAS-STING pathway contributes...
PurposeTo assess the effectiveness of robot-assisted training (RAT) plus acupuncture therapy (AT) on lower limb functional recovery in stroke patients...
Sex estimation represents a fundamental step in forensic identification protocols, traditionally relying on morphoscopic pelvic assessment. However, t...
Clinical research published in internal medicine journals relies heavily on statistical analysis and quantitative inference, making the quality of sta...
Recent advancements in Convolutional Neural Networks (CNNs), combined with the growing adoption of farm-applicable Internet of Things (IoT) devices, h...
Conventional sports anticipation studies primarily rely on hypothesis-testing paradigms that target predetermined cues. However, such approaches risk ...
As Moore's-law-driven geometric scaling nears physical, economic, and sustainability limits, semiconductor progress is increasingly constrained by the...
BACKGROUND: Large language models (LLMs) are increasingly used in biomedical research for statistical support, yet their reliability in selecting appr...
We aim to demonstrate the therapeutic value of the physical examination beyond its diagnostic function and to examine theoretical pathways that contri...