Hematology

A Comparison of Clinical Outcomes Between Two Different Models of Surgical Robots in Roux-en-Y Gastric Bypass.

For the past 20 years, robotic surgical systems have been used for the Roux-en-Y gastric bypass (RYGB). The da Vinci Surgical System (Intuitive Surgical, Inc.) has been one of the most used robotic platforms. This study aims to retrospectively compare the performance of two models of surgical robots. A retrospective comparative study was conducted from a prospective database including all patien...

Development and validation of the metric-based assessment of a robotic vessel dissection, vessel loop positioning, clip applying and bipolar coagulation task on an avian model.

The evolution of robotic technology and its diffusion does not seem to have been adequately accompanied by the development and implementation of surgeon training programs that ensure skilled and safe device use at the start of the learning curve. The objective of the study is to develop and validate performance metrics for vessel dissection, vessel loop positioning, clip applying and bipolar coagu...

Potential of high dimensional radiomic features to assess blood components in intraaortic vessels in non-contrast CT scans.

BACKGROUND: To assess the potential of radiomic features to quantify components of blood in intraaortic vessels to non-invasively predict moderate-to-...

Estimated Artificial Neural Network Modeling of Maximal Oxygen Uptake Based on Multistage 10-m Shuttle Run Test in Healthy Adults.

We aimed to develop an artificial neural network (ANN) model to estimate the maximal oxygen uptake (VOmax) based on a multistage 10 m shuttle run test...

Robust Blood Cell Image Segmentation Method Based on Neural Ordinary Differential Equations.

For the analysis of medical images, one of the most basic methods is to diagnose diseases by examining blood smears through a microscope to check the ...

Towards precision cardiometabolic prevention: results from a machine learning, semi-supervised clustering approach in the nationwide population-based ORISCAV-LUX 2 study.

Given the rapid increase in the incidence of cardiometabolic conditions, there is an urgent need for better approaches to prevent as many cases as pos...

Cell Mechanics Based Computational Classification of Red Blood Cells Via Machine Intelligence Applied to Morpho-Rheological Markers.

Despite fluorescent cell-labelling being widely employed in biomedical studies, some of its drawbacks are inevitable, with unsuitable fluorescent prob...

Imputation of the continuous arterial line blood pressure waveform from non-invasive measurements using deep learning.

In two-thirds of intensive care unit (ICU) patients and 90% of surgical patients, arterial blood pressure (ABP) is monitored non-invasively but interm...

An artificial intelligence-assisted diagnostic platform for rapid near-patient hematology.

Hematology analyzers capable of performing complete blood count (CBC) have lagged in their prevalence at the point-of-care. Sight OLO (Sight Diagnosti...

Application of Radiomics and Artificial Intelligence for Lung Cancer Precision Medicine.

Medical imaging is the standard-of-care for early detection, diagnosis, treatment planning, monitoring, and image-guided interventions of lung cancer ...

Test clamp procedure in robot-assisted partial nephrectomy: is it a safe procedure?

We performed test clamp procedure in robot-assisted partial nephrectomy (RAPN) to prevent massive bleeding during tumor resection and to omit dissecti...

Deep Semantic Segmentation Feature-Based Radiomics for the Classification Tasks in Medical Image Analysis.

Recently, an emerging trend in medical image classification is to combine radiomics framework with deep learning classification network in an integrat...

Assessing the Adequacy of Hemodialysis Patients via the Graph-Based Takagi-Sugeno-Kang Fuzzy System.

Maintenance hemodialysis is the main method for the treatment of end-stage renal disease in China. The / value is the gold standard of hemodialysis ad...

Automatic identification of malaria and other red blood cell inclusions using convolutional neural networks.

Malaria is a serious disease responsible for thousands of deaths each year. Many efforts have been made to aid in the diagnosis of malaria using machi...

Accurate Machine-Learning-Based classification of Leukemia from Blood Smear Images.

BACKGROUND: Conventional identification of blood disorders based on visual inspection of blood smears through microscope is time consuming, error-pron...

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. Patients suffering type 1 diabetes depend on the appr...

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 disease. The conventional analysis of bone marrow sme...

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, deep vein thrombosis (DVT) and its potential fatal ...

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 electronic health records (EHRs) offers a unique oppo...

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