HIV/AIDS

Effective and efficient neural networks for spike inference from calcium imaging.

Calcium imaging provides advantages in monitoring large populations of neuronal activities simultaneously. However, it lacks the signal quality provided by neural spike recording in traditional electrophysiology. To address this issue, we developed a supervised data-driven approach to extract spike information from calcium signals. We propose the ENS (effective and efficient neural networks for sp...

Self-Attention Based Neural Network for Predicting RNA-Protein Binding Sites.

Proteins binding to Ribonucleic Acid (RNA) inside cells are called RNA-binding proteins (RBP), which play a crucial role in gene regulation. The identification of RNA-protein binding sites helps to understand the function of RBP better. Although many computational methods have been developed to predict RNA-protein binding sites, their prediction accuracy on small sample datasets needs improvement....

A Deep-Learning-Computed Cancer Score for the Identification of Human Hepatocellular Carcinoma Area Based on a Six-Colour Multiplex Immunofluorescence Panel.

Liver cancer is one of the most frequently diagnosed and fatal cancers worldwide, with hepatocellular carcinoma (HCC) being the most common primary li...

Evaluation of the Impact of the Sustainable Development Goals on an Activity Recognition Platform for Healthcare Systems.

The Sustainable Development Goals (SDGs), also known as the Global Goals, were adopted by the United Nations in 2015 as a universal call to end povert...

Wayfinding artificial intelligence to detect clinically meaningful spots of retinal diseases: Artificial intelligence to help retina specialists in real world practice.

AIM/BACKGROUND: To aim of this study is to develop an artificial intelligence (AI) that aids in the thought process by providing retinal clinicians wi...

Accurate Prediction of Transcriptional Activity of Single Missense Variants in HIV Tat with Deep Learning.

Tat is an essential gene for increasing the transcription of all HIV genes, and affects HIV replication, HIV exit from latency, and AIDS progression. ...

Explainable AI in medical imaging: An overview for clinical practitioners - Beyond saliency-based XAI approaches.

Driven by recent advances in Artificial Intelligence (AI) and Computer Vision (CV), the implementation of AI systems in the medical domain increased c...

DeepDetect: Deep Learning of Peptide Detectability Enhanced by Peptide Digestibility and Its Application to DIA Library Reduction.

In tandem mass spectrometry-based proteomics, proteins are digested into peptides by specific protease(s), but generally only a fraction of peptides c...

Natural language processing in radiology: Clinical applications and future directions.

Natural language processing (NLP) is a wide range of techniques that allows computers to interact with human text. Applications of NLP in everyday lif...

Quantifying Inflammatory Response and Drug-Aided Resolution in an Atopic Dermatitis Model with Deep Learning.

Noninvasive quantification of dermal diseases aids efficacy studies and paves the way for broader enrollment in clinical studies across varied demogra...

Restoring speech intelligibility for hearing aid users with deep learning.

Almost half a billion people world-wide suffer from disabling hearing loss. While hearing aids can partially compensate for this, a large proportion o...

Sooty Tern Optimization Algorithm-Based Deep Learning Model for Diagnosing NSCLC Tumours.

Lung cancer is one of the most common causes of cancer deaths in the modern world. Screening of lung nodules is essential for early recognition to fac...

CXR-Net: A Multitask Deep Learning Network for Explainable and Accurate Diagnosis of COVID-19 Pneumonia From Chest X-Ray Images.

Accurate and rapid detection of COVID-19 pneumonia is crucial for optimal patient treatment. Chest X-Ray (CXR) is the first-line imaging technique for...

DR.BENCH: Diagnostic Reasoning Benchmark for Clinical Natural Language Processing.

The meaningful use of electronic health records (EHR) continues to progress in the digital era with clinical decision support systems augmented by art...

Do artificial neural networks love sex? How the combination of artificial neural networks with evolutionary algorithms may help to identify gender influence in rheumatic diseases.

Although medical research has been performed predominantly on men both in preclinical and clinical studies, continuous efforts have been made to overc...

Diagnosis of Multiple Faults in Rotating Machinery Using Ensemble Learning.

Fault diagnosis of rotating machines is an important task to prevent machinery downtime, and provide verifiable support for condition-based maintenanc...

Rapid simultaneous analysis of anti human immunodeficiency virus drugs in pharmaceutical formulation by smart spectrophotometry based on multivariate calibration and least squares support vector machine methods.

In this study, two chemometrics methods, including partial least squares regression (PLS) and least squares support vector machine (LS-SVM) were appli...

Prediction and Construction of Energetic Materials Based on Machine Learning Methods.

Energetic materials (EMs) are the core materials of weapons and equipment. Achieving precise molecular design and efficient green synthesis of EMs has...

The design of compounds with desirable properties - The anti-HIV case study.

Efficacy and safety are among the most desirable characteristics of an ideal drug. The tremendous increase in computing power and the entry of artific...

Planetary Mapping Using Deep Learning: A Method to Evaluate Feature Identification Confidence Applied to Habitats in Mars-Analog Terrain.

The goals of Mars exploration are evolving beyond describing environmental habitability at global and regional scales to targeting specific locations ...