Alternative Medicine

Multi-omics and machine learning framework reveals ABCG2 as a therapeutic target of Eleven Flavored Shenqi Tablets in clear cell renal cell carcinoma.

ETHNOPHARMACOLOGICAL RELEVANCE: Eleven Flavored Shenqi Tablets (EFST) is a classical multi-herbal prescription in traditional Chinese medicine, traditionally prescribed for kidney tonification and systemic regulation. Despite its reported anti-inflammatory and antiproliferative properties, the therapeutic value of EFST in clear cell renal cell carcinoma (ccRCC) remains unclear. METHODS: We integra...

(Some) Benefits in Operator Decisions to Use AI After Experiencing Optimal Outcomes.

ObjectiveThe current study aimed to explore the impacts of experiencing superior behaviors-accumulating large amounts of evidence and high automation use rates-on subsequent evidence accumulation rates and adaptable (discretionary) automation use decisions in a dynamic decision-making task.BackgroundOperators prefer to choose when to engage automated support systems but seldom use them appropriate...

Integrating network pharmacology and multidimensional bioinformatics: Mechanistic exploration of six food and medicine homology plants in coronary heart disease therapy.

Our study integrates network pharmacology with multiple bioinformatics approaches to systematically construct a framework for elucidating the therapeu...

Domain adaptive underwater object detection via complementary style-aware learning.

Images from different underwater domains exhibit multi-style variations caused by water quality, lighting, and imaging devices. The domain gap caused ...

Harnessing the application of artificial intelligence in identification of traditional Chinese medicines.

ETHNOPHARMACOLOGICAL RELEVANCE: The integration of artificial intelligence (AI) into pharmaceutical practice represents a paradigm shift, offering inn...

Artificial Intelligence for Postoperative Wound Monitoring: An Integrative Review of Digital Innovation and Clinical Feasibility.

Artificial intelligence (AI) has transformative potential in postoperative wound care through precise, automated, and timely wound assessment, yet spe...

Uncovering the therapeutic potential of Si-Miao-Yong-An decoction in abdominal aortic aneurysm: An integrative study combining network pharmacology, machine learning, molecular docking and dynamics simulation.

Abdominal aortic aneurysm (AAA) is a progressive and life-threatening vascular disorder characterized by abnormal dilation of the abdominal aorta and ...

Habitat-aware radiomics and adaptive 2.5D deep learning predict treatment response and long-term survival in ESCC patients undergoing neoadjuvant chemoimmunotherapy.

PURPOSE: Current radiomic approaches inadequately resolve spatial intratumoral heterogeneity (ITH) in esophageal squamous cell carcinoma (ESCC), limit...

Longitudinal multi-omics analysis of umbilical cord blood and childhood serum in Autism.

There is considerable evidence implicating maternal immune activation (MIA) and cytokine dysregulation in the pathophysiology of Autism. However, cyto...

Decoding the gut microbiota metabolite-matrix metalloproteinase-3 axis in breast cancer: a multi-omics and network pharmacology study.

Breast cancer is a malignant tumor originating from the breast epithelium, and emerging evidence suggests that the gut microbiota influences its devel...

Recent biotechnological advances in bioprospecting secondary metabolites from endolichenic fungi for drug discovery applications.

Endolichenic fungi (ELF) are symbiotic organisms residing in lichens. Since the initial report of its application in natural products and drug discove...

Convergence: Multi-omics and AI are reshaping the landscape biomedical research.

This special volume of Biochimica et Biophysica Acta - Molecular Basis of Disease showcases a transformative era in biomedical research, driven by the...

Efficient lightweight CNN for automated classification of B-cell acute lymphoblastic leukemia.

B-cell acute lymphoblastic leukemia (B-ALL) is an aggressive hematological malignancy that primarily affects children but can also occur in adults, pr...

Use of Machine Learning to Derive Discrete Clinical Phenotypes and Assess Treatment-Effect Heterogeneity in the Steroids in Cardiac Surgery Trial Dataset.

BACKGROUND: Robust clinical trial data provide a key component for the development of evidence-informed medicine. However, clinical trial data may dem...

Semi-supervised Medical Image Segmentation Using Heterogeneous Complementary Correction Network and Confidence Contrastive Learning.

Semi-supervised medical image segmentation techniques have demonstrated significant potential and effectiveness in clinical diagnosis. The prevailing ...

Foundation models for radiology: fundamentals, applications, opportunities, challenges, risks, and prospects.

Foundation models (FMs) represent a significant evolution in artificial intelligence (AI), impacting diverse fields. Within radiology, this evolution ...

Deep learning diagnosis plus kinematic severity assessments of neurodivergent disorders.

Early diagnostic assessments of neurodivergent disorders (NDD), remains a major clinical challenge. We address this problem by pursuing the hypothesis...

Virtual Humans in Geriatric Care: An Integrative Review.

BACKGROUND: The Fourth and Fifth Industrial Revolutions have introduced new and innovative technologies, such as artificial intelligence and virtual h...

Automated identification of spotted-fever tick vectors using convolutional neural networks.

Ticks are key ectoparasites for the One Health approach, as they are vectors of pathogens that infect humans, domestic and wild animals. The bacteria ...

Integrating MobileNetV3 and SqueezeNet for Multi-class Brain Tumor Classification.

Brain tumors pose a critical health threat requiring timely and accurate classification for effective treatment. Traditional MRI analysis is labor-int...