Alternative Medicine

Virtual Clinical Trials: Implications of Computer Simulations and Artificial Intelligence for Musculoskeletal Research.

In silico clinical trials, particularly when augmented with artificial intelligence methods, represe...

Assessing inclusion and representativeness on digital platforms for health education: Evidence from YouTube.

BACKGROUND: Studies confirm that significant biases exist in online recommendation platforms, exacer...

Machine learning and integrative multi-omics network analysis for survival prediction in acute myeloid leukemia.

BACKGROUND: Acute myeloid leukemia (AML) is the most common malignant myeloid disorder in adults and...

Machine learning integrative approaches to advance computational immunology.

The study of immunology, traditionally reliant on proteomics to evaluate individual immune cells, ha...

Discovery of a Novel and Potent LCK Inhibitor for Leukemia Treatment via Deep Learning and Molecular Docking.

The lymphocyte-specific protein tyrosine kinase (LCK) plays a crucial role in both T-cell developmen...

Apoptosis and NETotic cell death affect diabetic nephropathy independently: An study integrative study encompassing bioinformatics, machine learning, and experimental validation.

OBJECTIVE: Although programmed cell death (PCD) and diabetic nephropathy (DN) are intrinsically conn...

Identifying miRNA as biomarker for breast cancer subtyping using association rule.

- This paper presents a comprehensive study focused on breast cancer subtyping, utilizing a multifac...

A syntactic evidence network model for fact verification.

In natural language processing, fact verification is a very challenging task, which requires retriev...

The utility of artificial intelligence in identifying radiological evidence of lung cancer and pulmonary tuberculosis in a high-burden tuberculosis setting.

BACKGROUND: Artificial intelligence (AI), using deep learning (DL) systems, can be utilised to detec...

Do green finance and green innovation affect corporate credit rating performance? Evidence from machine learning approach.

This study investigates the impact of green finance (GF) and green innovation (GI) on corporate cred...

Leveraging AI to improve evidence synthesis in conservation.

Systematic evidence syntheses (systematic reviews and maps) summarize knowledge and are used to supp...

Developing a machine learning model for predicting venlafaxine active moiety concentration: a retrospective study using real-world evidence.

BACKGROUND: Venlafaxine is frequently prescribed for patients with depression. To control the concen...

Protocol to perform integrative analysis of high-dimensional single-cell multimodal data using an interpretable deep learning technique.

The advent of single-cell multi-omics sequencing technology makes it possible for researchers to lev...

Advancing intrauterine adhesion severity prediction: Integrative machine learning approach with hysteroscopic cold knife system, clinical characteristics and hematological parameters.

Intrauterine Adhesion (IUA) constitute a significant determinant impacting female fertility, potenti...

Automated identification of aquatic insects: A case study using deep learning and computer vision techniques.

Deep learning techniques have recently found application in biodiversity research. Mayflies (Ephemer...

Does the evidence exist for the deployment of AI in cancer therapies?

Predictive Models for Suicide Attempts in Major Depressive Disorder and the Contribution of : A Pilot Integrative Machine Learning Study.

Suicide is a major public health problem caused by a complex interaction of various factors. Major d...

A comprehensive analysis of key factors' impact on environmental performance: Evidence from Globe by novel super learner algorithm.

This study aims to analyze comprehensively the impact of different economic and demographic factors,...

Frequently asked questions on erectile dysfunction: evaluating artificial intelligence answers with expert mentorship.

The present study assessed the accuracy of artificiaI intelligence-generated responses to frequently...

Genome-scale metabolic models in translational medicine: the current status and potential of machine learning in improving the effectiveness of the models.

The genome-scale metabolic model (GEM) has emerged as one of the leading modeling approaches for sys...

Assessing the Capability of Large Language Models in Naturopathy Consultation.

Background The rapid advancements in natural language processing have brought about the widespread u...