COVID-19

IDH Mutation Classification in Nonenhancing Gliomas: A Comparison of Habitat and Whole-Tumor Transfer Learning Strategies.

BACKGROUND: Isocitrate dehydrogenase (IDH) mutation status is an important biomarker for the diagnosis and management of nonenhancing gliomas, underscoring the need for noninvasive preoperative classification. PURPOSE: To compare the value of habitat-based and whole-tumor strategies in classifying IDH mutation status in nonenhancing gliomas via transfer learning on structural magnetic resonance im...

Bridging the variant-to-function gap in type 2 diabetes: advances and challenges.

Type 2 diabetes is a polygenic, heterogeneous disease affecting over 530 million individuals worldwide, a number projected to rise to 1.3 billion by 2050. Genome-wide association studies have identified over 1200 loci associated with type 2 diabetes, yet only a modest proportion of disease heritability has been explained, and most risk variants lie in non-coding regions, complicating biological in...

Molecular targeted therapies, omics, and AI based theranostics approaches for the treatment of prostate cancer.

Cancer is a disease that begins with genetic and epigenetic alterations occurring in specific cells, some of which can spread and migrate to other tis...

MeNet: A mixed-effect deep neural network for multi-environment genomic prediction of agronomic traits.

Accurate genomic prediction of agronomic traits is critical for modern breeding and agriculture. Deep learning has great potential to enhance predicti...

From sample to clinical insight: a review of exome sequencing in disease diagnostics.

Exome sequencing (ES) has transformed genomic research and clinical diagnostics by enabling precise identification of disease-associated variants with...

Immunofixation electrophoresis image interpretation using transfer learning method.

INTRODUCTION: Immunofixation electrophoresis (IFE) is the gold standard for identifying monoclonal proteins in plasma cell disorders, but its interpre...

BRAIN-MAGNET: A functional genomics atlas for interpretation of non-coding variants.

Genome-wide assessment of genetic variation is becoming routine in genetics, yet functional interpretation of non-coding single nucleotide variants in...

Deep Learning-Assisted Prediction of Air-Bone Gap Using Tympanic Membrane Perforation Image Features.

OBJECTIVE: To evaluate a deep learning (DL)-based approach for predicting air-bone gap (ABG) from tympanic membrane (TM) perforation images using auto...

Emerging options and future strategies in immunotherapy for advanced lung squamous-cell carcinoma.

Advanced-stage lung squamous-cell carcinoma (LUSC) remains a therapeutic challenge. Although immune checkpoint inhibitors (ICIs) have revolutionized L...

Automatic measurement of pharyngeal contraction ratio during deglutition using 2D cine MRI with deep learning: A pilot study.

This study aimed to develop a deep learning-based method for automatic segmentation of the pharyngeal area (PA) and measurement of the pharyngeal cont...

Estimating the pupal age of Dermestes ater (Coleoptera: Dermestidae) using Fourier transform infrared spectroscopy combined with Chemometrics.

Necrophagous flies and beetles represent the two most forensically significant insect taxa. The pupal stage of beetles typically exhibits a longer dev...

Machine learning-assisted high-performance immunoSERS platform using silk fibroin as a natural etching mask for early diagnosis of Alzheimer's disease.

Early and accurate diagnosis of Alzheimer's disease (AD) is a major stride toward pharmacological interventions to delay the onset or progression of t...

Predictive surveillance and diagnosis of COVID-19: An integrative machine learning and wastewater multi-omics approach.

COVID-19 has had major global impacts, highlighting the importance of robust predictive surveillance and diagnostic systems to ensure effective public...

Machine learning differentiates right posterior from right anterior accessory pathways using 6-lead electrocardiograms in dogs with ventricular preexcitation.

OBJECTIVE: To develop a machine learning (ML) model to identify fiducial points on canine ECGs to localize right-sided accessory pathways as posterior...

Artificial intelligence-powered signal analysis of loop-mediated isothermal amplification (LAMP) for the screening of Kaposi sarcoma at the point of care.

Unlike the polymerase chain reaction (PCR), loop-mediated isothermal amplification (LAMP) lacks a consistent thermal cycle, making quantification part...

Benchmarking AlphaMissense against ClinVar for Diagnostic Interpretation of Missense Variants in Inherited Retinal Diseases.

PURPOSE: AlphaMissense is a newer deep learning-based variant predictor that evaluates the structural consequences of missense variants, the most comm...

Pathologic assessment of resected stage III non-small cell lung cancer after neoadjuvant chemotherapy: identification of additional prognostic factors.

BACKGROUND: Non-small cell lung cancer (NSCLC) patients undergoing neoadjuvant chemotherapy (NACT) followed by surgery represent an ideal clinical set...

Structure-Based Classification of CRISPR/Cas9 Proteins: A Machine Learning Approach to Elucidating Cas9 Allostery.

The CRISPR/Cas9 system is a powerful gene-editing tool. Its specificity and stability rely on complex allosteric regulation. Understanding these allos...

Patients visits forecasting in emergency departments: Self-adapting LSTM models for evolving data distributions.

BACKGROUND AND OBJECTIVE: Overcrowding in emergency departments (EDs) remains a critical challenge in healthcare systems. Accurate forecasting of pati...

Construction and validation of a hypertensive nephropathy diagnostic model based on mitochondrial-related genes using machine learning combined with WGCNA.

BACKGROUND: Hypertensive nephropathy (HTN) arises from chronic hypertension and may potentially result in severe renal failure. Due to the absence of ...