Hematology

Diagnosis of Asthma Based on Routine Blood Biomarkers Using Machine Learning.

Intelligent medical diagnosis has become common in the era of big data, although this technique has ...

Prediction of hypertension, hyperglycemia and dyslipidemia from retinal fundus photographs via deep learning: A cross-sectional study of chronic diseases in central China.

Retinal fundus photography provides a non-invasive approach for identifying early microcirculatory a...

Using Machine Learning to Predict Early Onset Acute Organ Failure in Critically Ill Intensive Care Unit Patients With Sickle Cell Disease: Retrospective Study.

BACKGROUND: Sickle cell disease (SCD) is a genetic disorder of the red blood cells, resulting in mul...

Intelligent classification of platelet aggregates by agonist type.

Platelets are anucleate cells in blood whose principal function is to stop bleeding by forming aggre...

An Effective Convolutional Neural Network for Classifying Red Blood Cells in Malaria Diseases.

Malaria is one of the epidemics that can cause human death. Accurate and rapid diagnosis of malaria ...

Deep learning-based monocular placental pose estimation: towards collaborative robotics in fetoscopy.

PURPOSE: Twin-to-twin transfusion syndrome (TTTS) is a placental defect occurring in monochorionic t...

Expert-level automated malaria diagnosis on routine blood films with deep neural networks.

Over 200 million malaria cases globally lead to half a million deaths annually. Accurate malaria dia...

Convolutional Neural Network Can Recognize Drug Resistance of Single Cancer Cells.

It is known that single or isolated tumor cells enter cancer patients' circulatory systems. These ci...

FetNet: a recurrent convolutional network for occlusion identification in fetoscopic videos.

PURPOSE: Fetoscopic laser photocoagulation is a minimally invasive surgery for the treatment of twin...

Artificial Intelligence: The Future for Diabetes Care.

Artificial intelligence (AI) is a fast-growing field and its applications to diabetes, a global pand...

End-to-End Deep Learning Architecture for Continuous Blood Pressure Estimation Using Attention Mechanism.

Blood pressure (BP) is a vital sign that provides fundamental health information regarding patients....

Combination Strategies for Immune-Checkpoint Blockade and Response Prediction by Artificial Intelligence.

The therapeutic concept of unleashing a pre-existing immune response against the tumor by the applic...

Early-Stage Lung Cancer Diagnosis by Deep Learning-Based Spectroscopic Analysis of Circulating Exosomes.

Lung cancer has a high mortality rate, but an early diagnosis can contribute to a favorable prognosi...

Development of a prediction model for hypotension after induction of anesthesia using machine learning.

Arterial hypotension during the early phase of anesthesia can lead to adverse outcomes such as a pro...

Brain tumor classification of virtual NMR voxels based on realistic blood vessel-induced spin dephasing using support vector machines.

Remodeling of tissue microvasculature commonly promotes neoplastic growth; however, there is no imag...

Development of machine learning and natural language processing algorithms for preoperative prediction and automated identification of intraoperative vascular injury in anterior lumbar spine surgery.

BACKGROUND: Intraoperative vascular injury (VI) may be an unavoidable complication of anterior lumba...

Detection of Rare Objects by Flow Cytometry: Imaging, Cell Sorting, and Deep Learning Approaches.

Flow cytometry nowadays is among the main working instruments in modern biology paving the way for c...

Regarding: Shung et al: Validation of a Machine Learning Model That Outperforms Clinical Risk Scoring Systems for Upper Gastrointestinal Bleeding.

RE: Validation of a Machine Learning Model That Outperforms Clinical Risk Scoring Systems for Upper Gastrointestinal Bleeding.

A neural network approach for real-time particle/cell characterization in microfluidic impedance cytometry.

Microfluidic applications such as active particle sorting or selective enrichment require particle c...

Sequential classification system for recognition of malaria infection using peripheral blood cell images.

AIMS: Morphological recognition of red blood cells infected with malaria parasites is an important t...