COVID-19

Integrated CNN and Federated Learning for COVID-19 Detection on Chest X-Ray Images.

Currently, Coronavirus Disease 2019 (COVID-19) is still endangering world health and safety and deep...

Synthesis of higher-B CEST Z-spectra from lower-B data via deep learning and singular value decomposition.

Chemical exchange saturation transfer (CEST) MRI at 3 T suffers from low specificity due to overlapp...

Rapid In Situ Near-Infrared Assessment of Tetrahydrocannabinolic Acid in Cannabis Inflorescences before Harvest Using Machine Learning.

Cannabis is cultivated for therapeutic and recreational purposes where delta-9 tetrahydrocannabinol ...

Polygonal Approximation Learning for Convex Object Segmentation in Biomedical Images With Bounding Box Supervision.

As a common and critical medical image analysis task, deep learning based biomedical image segmentat...

Quantitative drug susceptibility testing for Mycobacterium tuberculosis using unassembled sequencing data and machine learning.

There remains a clinical need for better approaches to rapid drug susceptibility testing in view of ...

Automated segmentation in pelvic radiotherapy: A comprehensive evaluation of ATLAS-, machine learning-, and deep learning-based models.

Artificial intelligence can standardize and automatize highly demanding procedures, such as manual s...

Spectrochemical and explainable artificial intelligence approaches for molecular level identification of the status of critically ill patients with COVID-19.

This study explores the molecular alterations and disease progression in COVID-19 patients using ATR...

Machine learning predicts conventional imaging metastasis-free survival (MFS) for oligometastatic castration-sensitive prostate cancer (omCSPC) using prostate-specific membrane antigen (PSMA) PET radiomics.

PURPOSE: This study investigated imaging biomarkers derived from PSMA-PET acquired pre- and post-met...

The Lag -Effects of Air Pollutants and Meteorological Factors on COVID-19 Infection Transmission and Severity: Using Machine Learning Techniques.

BACKGROUND: Exposure to air pollution is a major health problem worldwide. This study aimed to inves...

Deep mutational scanning and machine learning for the analysis of antimicrobial-peptide features driving membrane selectivity.

Many antimicrobial peptides directly disrupt bacterial membranes yet can also damage mammalian membr...

Performance of artificial intelligence in predicting the prognossis of severe COVID-19: a systematic review and meta-analysis.

BACKGROUND: COVID-19-induced pneumonia has become a persistent health concern, with severe cases pos...

Self-learning neural network as a prediction model in non-invasive prenatal testing to detect fetal SNVs.

Mask region-based convolutional neural network and VGG-16 inspired brain tumor segmentation.

The process of brain tumour segmentation entails locating the tumour precisely in images. Magnetic R...

Shape prior-constrained deep learning network for medical image segmentation.

We propose a shape prior representation-constrained multi-scale features fusion segmentation network...

Testing behaviour change with an artificial intelligence chatbot in a randomized controlled study.

Chatbots can effect large-scale behaviour change because they are accessible through social media, f...

Adopting machine learning to predict ICU delirium.

With neuropsychiatric complications recognized among COVID-19 patients translating into significant ...

Machine-learning-assisted high-throughput identification of potent and stable neutralizing antibodies against all four dengue virus serotypes.

Several computational methods have been developed to identify neutralizing antibodies (NAbs) coverin...

Advancements in nanobody generation: Integrating conventional, in silico, and machine learning approaches.

Nanobodies, derived from camelids and sharks, offer compact, single-variable heavy-chain antibodies ...

Insights from EEG analysis of evoked memory recalls using deep learning for emotion charting.

Affect recognition in a real-world, less constrained environment is the principal prerequisite of th...

AI Hesitancy and Acceptability-Perceptions of AI Chatbots for Chronic Health Management and Long COVID Support: Survey Study.

BACKGROUND: Artificial intelligence (AI) chatbots have the potential to assist individuals with chro...

Deep representation learning from electronic medical records identifies distinct symptom based subtypes and progression patterns for COVID-19 prognosis.

OBJECTIVE: Symptoms are significant kind of phenotypes for managing and controlling of the burst of ...