COVID-19

AI-enabled alkaline-resistant evolution of protein to apply in mass production.

Artificial intelligence (AI) models have been used to study the compositional regularities of proteins in nature, enabling it to assist in protein design to improve the efficiency of protein engineering and reduce manufacturing cost. However, in industrial settings, proteins are often required to work in extreme environments where they are relatively scarce or even non-existent in nature. Since su...

Unveiling the potential of Brachiaria ruziziensis: Comparative analysis of multivariate and machine learning models for biomass and NPK prediction using Vis-NIR-SWIR spectroscopy.

This study investigated the development and validation of predictive models for estimating foliar nitrogen (N), phosphorus (P), and potassium (K) contents, along with shoot dry mass (SDM) of Brachiaria ruziziensis L. The approach utilized Vis-NIR-SWIR spectroscopy coupled with multivariate statistical techniques (PLS, PCR) and machine learning algorithms (SVM, RF). A triple-factorial, completely r...

Predicting Treatment Response of Repetitive Transcranial Magnetic Stimulation in Major Depressive Disorder Using an Explainable Machine Learning Model Based on Electroencephalography and Clinical Features.

Major depressive disorder (MDD) is highly heterogeneous in response to repetitive transcranial magnetic stimulation (rTMS), and identifying predictive...

Identification of biomarkers in Alzheimer's disease and COVID-19 by bioinformatics combining single-cell data analysis and machine learning algorithms.

BACKGROUND: Since its emergence in 2019, COVID-19 has become a global epidemic. Several studies have suggested a link between Alzheimer's disease (AD)...

Bridging Neuroscience and Machine Learning: A Gender-Based Electroencephalogram Framework for Guilt Emotion Identification.

This study explores the link between the emotion "guilt" and human EEG data, and investigates the influence of gender differences on the expression of...

A unique AI-based tool for automated segmentation of pulp cavity structures in maxillary premolars on CBCT.

To develop and validate an artificial intelligence (AI)-driven tool for the automatic segmentation of pulp cavity structures in maxillary premolars te...

Hybrid-RViT: Hybridizing ResNet-50 and Vision Transformer for Enhanced Alzheimer's disease detection.

Alzheimer's disease (AD) is a leading cause of disability worldwide. Early detection is critical for preventing progression and formulating effective ...

Early detection of disease outbreaks and non-outbreaks using incidence data: A framework using feature-based time series classification and machine learning.

Forecasting the occurrence and absence of novel disease outbreaks is essential for disease management, yet existing methods are often context-specific...

Comparative analysis of machine learning models for predicting pathological complete response to neoadjuvant chemotherapy in breast cancer: An MRI radiomics approach.

PURPOSE: The aim of this work is to compare different machine learning models for predicting pathological complete response (pCR) to neoadjuvant chemo...

Automated grading of oleaster fruit using deep learning.

The agriculture sector is crucial to many economies, particularly in developing regions, with post-harvest technology emerging as a key growth area. T...

Accuracy of Commercial Large Language Model (ChatGPT) to Predict the Diagnosis for Prehospital Patients Suitable for Ambulance Transport Decisions: Diagnostic Accuracy Study.

OBJECTIVES: While ambulance transport decisions guided by artificial intelligence (AI) could be useful, little is known of the accuracy of AI in makin...

DeepInterAware: Deep Interaction Interface-Aware Network for Improving Antigen-Antibody Interaction Prediction from Sequence Data.

Identifying interactions between candidate antibodies and target antigens is a key step in developing effective human therapeutics. The antigen-antibo...

Data-Driven Insights into Resin Screening for Targeted Per- and Polyfluoroalkyl Substances Removal Using Machine Learning.

In this study, we address the challenge of screening resins and optimizing operation conditions for the removal of 43 perfluoroalkyl and polyfluoroalk...

Hyperspectral technology and machine learning models to estimate the fruit quality parameters of mango and strawberry crops.

Using chemical laboratory procedures to estimate the fruit quality parameters (biochemical parameters) of mango "Succarri" and strawberry "Florida" as...

Forecasting Epidemic Spread With Recurrent Graph Gate Fusion Transformers.

Predicting the unprecedented, nonlinear nature of COVID-19 presents a significant public health challenge. Recent advances in deep learning, such as g...

Galactose-Induced Cataracts in Rats: A Machine Learning Analysis.

Rat models are widely used to study cataracts due to their cost-effectiveness and prominent physiological and genetic similarities to humans The obje...

Genome data based deep learning identified new genes predicting pharmacological treatment response of attention deficit hyperactivity disorder.

Although the efficacy of pharmacy in the treatment of attention deficit/hyperactivity disorder (ADHD) has been well established, the lack of predictor...

Using near-infrared hyperspectral imaging combined with machine learning to predict the components and the origin of Radix Paeoniae Rubra.

The efficacy and safety of drugs are closely related to the geographical origin and quality of the raw materials. This study focuses on using near-inf...

Unveiling the new chapter in nanobody engineering: advances in traditional construction and AI-driven optimization.

Nanobodies (Nbs), miniature antibodies consisting solely of the variable region of heavy chains, exhibit unique properties such as small size, high st...

Proficiency, Clarity, and Objectivity of Large Language Models Versus Specialists' Knowledge on COVID-19's Impacts in Pregnancy: Cross-Sectional Pilot Study.

BACKGROUND: The COVID-19 pandemic has significantly strained health care systems globally, leading to an overwhelming influx of patients and exacerbat...