Infectious Disease

COVID-19

Latest AI and machine learning research in covid-19 for healthcare professionals.

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Diagnostic Test Accuracy of Deep Learning Prediction Models on COVID-19 Severity: Systematic Review and Meta-Analysis.

BACKGROUND: Deep learning (DL) prediction models hold great promise in the triage of COVID-19.

Probing the origins of programmed death ligand-1 inhibition by implementing machine learning-assisted sequential virtual screening techniques.

PD-L1 is a key immunotarget involved in binding to its receptor PD-1. PD-L1/PD-1 interface blocking ...

Sparser spiking activity can be better: Feature Refine-and-Mask spiking neural network for event-based visual recognition.

Event-based visual, a new visual paradigm with bio-inspired dynamic perception and ÎĽs level temporal...

MRI-based deep learning model for differentiation of hepatic hemangioma and hepatoblastoma in early infancy.

UNLABELLED: Hepatic hemangioma (HH) and hepatoblastoma (HBL) are common pediatric liver tumors and p...

Detecting shortcut learning for fair medical AI using shortcut testing.

Machine learning (ML) holds great promise for improving healthcare, but it is critical to ensure tha...

A Review of the Systemic Manifestations of Hepatitis B Virus Infection, Hepatitis D Virus, Hepatocellular Carcinoma, and Emerging Therapies.

Chronic hepatitis B virus (HBV) infection affects about 262 million people worldwide, leading to ove...

Deep learning neural network derivation and testing to distinguish acute poisonings.

INTRODUCTION: Acute poisoning is a significant global health burden, and the causative agent is ofte...

Prediction of oxygen supplementation by a deep-learning model integrating clinical parameters and chest CT images in COVID-19.

PURPOSE: As of March 2023, the number of patients with COVID-19 worldwide is declining, but the earl...

Comparing machine learning algorithms to predict COVID‑19 mortality using a dataset including chest computed tomography severity score data.

Since the beginning of the COVID-19 pandemic, new and non-invasive digital technologies such as arti...

Initial Testing of Robotic Exoskeleton Hand Device for Stroke Rehabilitation.

The preliminary test results of a novel robotic hand rehabilitation device aimed at treatment for th...

A hierarchical self-attention-guided deep learning framework to predict breast cancer response to chemotherapy using pre-treatment tumor biopsies.

BACKGROUND: Pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) has demonstrated ...

Unsupervised domain adaptation for Covid-19 classification based on balanced slice Wasserstein distance.

Covid-19 has swept the world since 2020, taking millions of lives. In order to seek a rapid diagnosi...

Multimodal deep learning for COVID-19 prognosis prediction in the emergency department: a bi-centric study.

Predicting clinical deterioration in COVID-19 patients remains a challenging task in the Emergency D...

Evaluation of breast tumor morphologies from African American and Caucasian patients.

The primary aim of this research was to investigate potential differences of breast tumor morphologi...

Assessment of coastal vulnerability using integrated fuzzy analytical hierarchy process and geospatial technology for effective coastal management.

The vulnerability of coastal regions to climate change is a growing global concern, particularly in ...

Noninvasive genetic screening: current advances in artificial intelligence for embryo ploidy prediction.

This review discusses the use of artificial intelligence (AI) algorithms in noninvasive prediction o...

Artificial Intelligence-Assisted Diagnostic Cytology and Genomic Testing for Hematologic Disorders.

Artificial intelligence (AI) is a rapidly evolving field of computer science that involves the devel...

Acceptance of social assistant robots for the older adults living in the community in China.

BACKGROUND: Social assistant robots (SARs) are an important part of providing high quality health an...

Gene-specific machine learning for pathogenicity prediction of rare BRCA1 and BRCA2 missense variants.

Machine learning-based pathogenicity prediction helps interpret rare missense variants of BRCA1 and ...

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