Preventive Care

Artificial intelligence in pancreatic cancer.

Pancreatic cancer is the deadliest disease, with a five-year overall survival rate of just 11%. The pancreatic cancer patients diagnosed with early screening have a median overall survival of nearly ten years, compared with 1.5 years for those not diagnosed with early screening. Therefore, early diagnosis and early treatment of pancreatic cancer are particularly critical. However, as a rare diseas...

Development of non-bias phenotypic drug screening for cardiomyocyte hypertrophy by image segmentation using deep learning.

The number of patients with heart failure and related deaths is rapidly increasing worldwide, making it a major problem. Cardiac hypertrophy is a crucial preliminary step in heart failure, but its treatment has not yet been fully successful. In this study, we established a system to evaluate cardiomyocyte hypertrophy using a deep learning-based high-throughput screening system and identified drugs...

DENVIS: Scalable and High-Throughput Virtual Screening Using Graph Neural Networks with Atomic and Surface Protein Pocket Features.

Computational methods for virtual screening can dramatically accelerate early-stage drug discovery by identifying potential hits for a specified targe...

Development and validation of chest CT-based imaging biomarkers for early stage COVID-19 screening.

Coronavirus Disease 2019 (COVID-19) is currently a global pandemic, and early screening is one of the key factors for COVID-19 control and treatment. ...

Detection of Breast Cancer Lump and BRCA1/2 Genetic Mutation under Deep Learning.

To diagnose and cure breast cancer early, thus reducing the mortality of patients with breast cancer, a method was provided to judge threshold of imag...

Mammogram classification based on a novel convolutional neural network with efficient channel attention.

Early accurate mammography screening and diagnosis can reduce the mortality of breast cancer. Although CNN-based breast cancer computer-aided diagnosi...

Act Like a Radiologist: Towards Reliable Multi-View Correspondence Reasoning for Mammogram Mass Detection.

Mammogram mass detection is crucial for diagnosing and preventing the breast cancers in clinical practice. The complementary effect of multi-view mamm...

Comments on "Identifying psychological antecedents and predictors of vaccine hesitancy through machine learning: A cross sectional study among chronic disease patients of deprived urban neighbourhood, India".

Dear Editor, we read the publication by Rustagi et al. "Identifying psychological antecedents and predictors of vaccine hesitancy through machine lear...

Comprehensive review of publicly available colonoscopic imaging databases for artificial intelligence research: availability, accessibility, and usability.

BACKGROUND AND AIMS: Publicly available databases containing colonoscopic imaging data are valuable resources for artificial intelligence (AI) researc...

Acute colonic flexures: the basis for developing an artificial intelligence-based tool for predicting the course of colonoscopy.

Tortuosity of the colon is an important parameter for predicting the course of colonoscopy. Computed tomography scans of the abdominal cavity were per...

UC-NfNet: Deep learning-enabled assessment of ulcerative colitis from colonoscopy images.

Ulcerative colitis (UC) belongs to the inflammatory bowel disease (IBD) family, which is mainly caused by inflammation of the tissue in the colon and ...

Improvement of intervention information detection for automated clinical literature screening during systematic review.

Systematic literature review (SLR) is a crucial method for clinicians and policymakers to make their decisions in a flood of new clinical studies. Bec...

A novel hybrid approach for feature selection enhancement: COVID-19 case study.

Feature selection is a promising Artificial Intelligence technique for screening, analysing, predicting, and tracking current COVID-19 patients and li...

Field validation of deep learning based Point-of-Care device for early detection of oral malignant and potentially malignant disorders.

Early detection of oral cancer in low-resource settings necessitates a Point-of-Care screening tool that empowers Frontline-Health-Workers (FHW). This...

Diabetic retinopathy screening using deep learning for multi-class imbalanced datasets.

Screening and diagnosis of diabetic retinopathy disease is a well known problem in the biomedical domain. The use of medical imagery from a patient's ...

Deep Learning-Based Computed Tomography Features in Evaluating Early Screening and Risk Factors for Chronic Obstructive Pulmonary Disease.

This research aimed to investigate the diagnostic effect of computed tomography (CT) images based on a deep learning double residual convolution neura...

Robust automated prediction of the revised Vienna Classification in colonoscopy using deep learning: development and initial external validation.

BACKGROUND: Improved optical diagnostic technology is needed that can be used by also outside expert centers. Hence, we developed an artificial intell...

Identification of missing hierarchical relations in the vaccine ontology using acquired term pairs.

BACKGROUND: The Vaccine Ontology (VO) is a biomedical ontology that standardizes vaccine annotation. Errors in VO will affect a multitude of applicati...

Artificial Intelligence for Colonoscopy: Past, Present, and Future.

During the past decades, many automated image analysis methods have been developed for colonoscopy. Real-time implementation of the most promising met...

Double-Balanced Loss for Imbalanced Colorectal Lesion Classification.

Colorectal cancer has a high incidence rate in all countries around the world, and the survival rate of patients is improved by early detection. With ...