Hematology

Learning Carbohydrate Digestion and Insulin Absorption Curves Using Blood Glucose Level Prediction and Deep Learning Models.

Type 1 diabetes is a chronic disease caused by the inability of the pancreas to produce insulin. Pat...

A Machine Learning Tool Using Digital Microscopy (Morphogo) for the Identification of Abnormal Lymphocytes in the Bone Marrow.

Morphological analysis of the bone marrow is an essential step in the diagnosis of hematological dis...

Using Wearables and Machine Learning to Enable Personalized Lifestyle Recommendations to Improve Blood Pressure.

Blood pressure (BP) is an essential indicator for human health and is known to be greatly influence...

Ocular blood flow as it relates to race and disease on glaucoma.

Glaucoma is a multifactorial progressive and degenerative optic neuropathy representing one of the w...

Machine learning application for the prediction of SARS-CoV-2 infection using blood tests and chest radiograph.

Triaging and prioritising patients for RT-PCR test had been essential in the management of COVID-19 ...

An artificial neural network approach integrating plasma proteomics and genetic data identifies PLXNA4 as a new susceptibility locus for pulmonary embolism.

Venous thromboembolism is the third common cardiovascular disease and is composed of two entities, d...

Machine learning liver-injuring drug interactions with non-steroidal anti-inflammatory drugs (NSAIDs) from a retrospective electronic health record (EHR) cohort.

Drug-drug interactions account for up to 30% of adverse drug reactions. Increasing prevalence of ele...

Letter to the Editor: Quantitative evaluation of COVID-19 pneumonia severity by CT pneumonia analysis algorithm using deep learning technology and blood test results.

Predicting intraoperative bleeding in patients undergoing a hepatectomy using multiple machine learning and deep learning techniques.

Optical tissue clearing and machine learning can precisely characterize extravasation and blood vessel architecture in brain tumors.

Precise methods for quantifying drug accumulation in brain tissue are currently very limited, challe...

Augmented intelligence to predict 30-day mortality in patients with cancer.

An augmented intelligence tool to predict short-term mortality risk among patients with cancer coul...

Combining microfluidics with machine learning algorithms for RBC classification in rare hereditary hemolytic anemia.

Combining microfluidics technology with machine learning represents an innovative approach to conduc...

ABO blood group system and risk of positive surgical margins in patients treated with robot-assisted radical prostatectomy: results in 1114 consecutive patients.

To test the hypothesis of associations between the ABO blood group system (ABO-bg) and prostate canc...

Optical mesoscopy, machine learning, and computational microscopy enable high information content diagnostic imaging of blood films.

Automated image-based assessment of blood films has tremendous potential to support clinical haemato...

Combined deep CNN-LSTM network-based multitasking learning architecture for noninvasive continuous blood pressure estimation using difference in ECG-PPG features.

The pulse arrival time (PAT), the difference between the R-peak time of electrocardiogram (ECG) sign...

Construction and Validation of a Lung Cancer Diagnostic Model Based on 6-Gene Methylation Frequency in Blood, Clinical Features, and Serum Tumor Markers.

Lung cancer has a high mortality rate. Promoting early diagnosis and screening of lung cancer is the...

Risk prediction for delayed clearance of high-dose methotrexate in pediatric hematological malignancies by machine learning.

This study aimed to establish a predictive model to identify children with hematologic malignancy at...

Thiol modified bimodal mesoporous silica nanoparticles for removal and determination toxic vanadium from air and human biological samples in petrochemical workers.

Investigation of exposure to toxic vanadium (V) in petrochemical workers is very important for human...

Deepometry, a framework for applying supervised and weakly supervised deep learning to imaging cytometry.

Deep learning offers the potential to extract more than meets the eye from images captured by imagin...

Prediction of venous thromboembolism with machine learning techniques in young-middle-aged inpatients.

Accumulating studies appear to suggest that the risk factors for venous thromboembolism (VTE) among ...

Profiling single-cell level phagocytic activity distribution with blood lactate levels.

The ability to kill infecting microbes is an essential facet of our immune response to an infection....