Preventive Care

Advances in machine intelligence-driven virtual screening approaches for big-data.

Virtual screening (VS) is an integral and ever-evolving domain of drug discovery framework. The VS is traditionally classified into ligand-based (LB) and structure-based (SB) approaches. Machine intelligence or artificial intelligence has wide applications in the drug discovery domain to reduce time and resource consumption. In combination with machine intelligence algorithms, VS has emerged into ...

Structure-based approaches against COVID-19.

The coronavirus disease 2019 (COVID-19) pandemic has had a major impact on human life. This review highlights the versatile roles of both classical and modern structure-based approaches for COVID-19. X-ray crystallography, nuclear magnetic resonance spectroscopy, and cryogenic electron microscopy are the three cornerstones of classical structural biology. These technologies have helped provide fun...

Humoral Immune Responses after an Omicron-Adapted Booster BNT162b2 Vaccination in Patients with Lymphoid Malignancies.

To accommodate waning COVID-19 vaccine immunity to emerging SARS-CoV-2 variants, variant-adapted mRNA vaccines have been introduced. Here, we examine ...

Development and validation of a three-dimensional deep learning-based system for assessing bowel preparation on colonoscopy video.

BACKGROUND: The performance of existing image-based training models in evaluating bowel preparation on colonoscopy videos was relatively low, and only...

Enhancing artificial intelligence-doctor collaboration for computer-aided diagnosis in colonoscopy through improved digital literacy.

Establishing appropriate trust and maintaining a balanced reliance on digital resources are vital for accurate optical diagnoses and effective integra...

Optimizing Signal Management in a Vaccine Adverse Event Reporting System: A Proof-of-Concept with COVID-19 Vaccines Using Signs, Symptoms, and Natural Language Processing.

INTRODUCTION: The Vaccine Adverse Event Reporting System (VAERS) has already been challenged by an extreme increase in the number of individual case s...

An Uncertainty-Guided Deep Learning Method Facilitates Rapid Screening of CYP3A4 Inhibitors.

Cytochrome P450 3A4 (CYP3A4), a prominent member of the P450 enzyme superfamily, plays a crucial role in metabolizing various xenobiotics, including o...

A multimodal screening system for elderly neurological diseases based on deep learning.

In this paper, we propose a deep-learning-based algorithm for screening neurological diseases. We proposed various examination protocols for screening...

Colonoscopy setting and impact on statistical significance in Artificial Intelligence trials.

A Systematic Approach Focused on Machine Learning Models for Exploring the Landscape of Physiological Measurement and Estimation Using Photoplethysmography (PPG).

A non-invasive optical technique known as photoplethysmography (PPG) can be used to provide various physiological measurements and estimations. PPG ca...

The application of artificial intelligence in diabetic retinopathy screening: a Saudi Arabian perspective.

INTRODUCTION: Diabetic retinopathy (DR) is the leading cause of preventable blindness in Saudi Arabia. With a prevalence of up to 40% of patients with...

Diabetes and artificial intelligence beyond the closed loop: a review of the landscape, promise and challenges.

The discourse amongst diabetes specialists and academics regarding technology and artificial intelligence (AI) typically centres around the 10% of peo...

Experimental validation of immunogenic SARS-CoV-2 T cell epitopes identified by artificial intelligence.

During the COVID-19 pandemic we utilized an AI-driven T cell epitope prediction tool, the NEC Immune Profiler (NIP) to scrutinize and predict regions ...

COVID-19 Vaccination in Liver Cirrhosis: Safety and Immune and Clinical Responses.

INTRODUCTION: Three years after the beginning of the SARS-CoV-2 pandemic, the safety and efficacy of COVID-19 vaccination in liver cirrhosis (LC) pati...

Artificial Intelligence: From Buzzword to Useful Tool in Clinical Pharmacology.

The advent of artificial intelligence (AI) in clinical pharmacology and drug development is akin to the dawning of a new era. Previously dismissed as ...

Enhancing human-AI collaboration: The case of colonoscopy.

Diagnostic errors impact patient health and healthcare costs. Artificial Intelligence (AI) shows promise in mitigating this burden by supporting Medic...

A novel deep generative model for mRNA vaccine development: Designing 5' UTRs with 1-methyl-pseudouridine modification.

Efficient translation mediated by the 5' untranslated region (5' UTR) is essential for the robust efficacy of mRNA vaccines. However, the 1-methyl-pse...

Artificial intelligence: Machine learning approach for screening large database and drug discovery.

Recent research in drug discovery dealing with many faces difficulties, including development of new drugs during disease outbreak and drug resistance...

Automatic literature screening using the PAJO deep-learning model for clinical practice guidelines.

BACKGROUND: Clinical practice guidelines (CPGs) are designed to assist doctors in clinical decision making. High-quality research articles are importa...

Integration of Deep Learning and Sequential Metabolism to Rapidly Screen Dipeptidyl Peptidase (DPP)-IV Inhibitors from .

Traditional Chinese medicine (TCM) possesses unique advantages in the management of blood glucose and lipids. However, there is still a significant ga...