Hematology

How can artificial intelligence help rehabilitation programs for people with hemophilia in the coming decades?

Non-invasive arterial blood pressure measurement and SpO estimation using PPG signal: a deep learning framework.

BACKGROUND: Monitoring blood pressure and peripheral capillary oxygen saturation plays a crucial rol...

High-precision prediction of blood glucose concentration utilizing Fourier transform Raman spectroscopy and an ensemble machine learning algorithm.

Raman spectroscopy has gained popularity in analyzing blood glucose levels due to its non-invasive i...

Attention-based deep learning framework to recognize diabetes disease from cellular retinal images.

A medical disorder known as diabetic retinopathy (DR) affects people who suffer from diabetes. Many ...

Letter: Deep Neural Networks Can Accurately Detect Blood Loss and Hemorrhage Control Task Success from Video.

A Review of the Systemic Manifestations of Hepatitis B Virus Infection, Hepatitis D Virus, Hepatocellular Carcinoma, and Emerging Therapies.

Chronic hepatitis B virus (HBV) infection affects about 262 million people worldwide, leading to ove...

Clinical relevance of deep learning models in predicting the onset timing of cancer pain exacerbation.

Cancer pain is a challenging clinical problem that is encountered in the management of cancer pain. ...

A novel CS-NET architecture based on the unification of CNN, SVM and super-resolution spectrogram to monitor and classify blood pressure using photoplethysmography.

CONTEXT: Continuous blood pressure (BP) monitoring plays an important role while treating various ca...

Continuous Blood Pressure Monitoring in Patients Having Surgery: A Narrative Review.

Hypotension can occur before, during, and after surgery and is associated with postoperative complic...

Association of white blood cell count after operative vaginal delivery with maternal adverse outcome: A retrospective cohort study.

BACKGROUND: The white blood cell count is often used to assess the maternal condition after an opera...

Impact of Additional Administration of von Willebrand Factor Concentrates to Thrombocyte Transfusion in Perioperative Bleeding in Cardiac Surgery.

BACKGROUND: Von Willebrand factor (vWF) is an important part of blood coagulation since it binds pla...

Propensity-matched analysis of robotic versus sternotomy approaches for mitral valve replacement.

To compare early and medium-term outcomes between robotic and sternotomy approaches for mitral valve...

Artificial intelligence-generated peripheral blood film images using generative adversarial networks and diffusion models.

Open versus robot-assisted partial nephrectomy for highly complex renal masses: a meta-analysis of perioperitive and functional outcomes.

Robot-assisted partial nephrectomy (RAPN) is increasingly being used for the complex surgical manage...

Glucose-6-phosphate dehydrogenase deficiency with coinherited Gaucher disease: A rare association.

Anemia coexisting with Gaucher disease (GD) is often associated with non-hemolytic processes. Few ca...

Multimodal deep learning for COVID-19 prognosis prediction in the emergency department: a bi-centric study.

Predicting clinical deterioration in COVID-19 patients remains a challenging task in the Emergency D...

Magnetically actuated hydrogel-based capsule microrobots for intravascular targeted drug delivery.

Microrobots for targeted drug delivery in blood vessels have attracted increasing interest from rese...

In Reply: Deep Neural Networks Can Accurately Detect Blood Loss and Hemorrhage Control Task Success from Video.

Artificial Intelligence-Assisted Diagnostic Cytology and Genomic Testing for Hematologic Disorders.

Artificial intelligence (AI) is a rapidly evolving field of computer science that involves the devel...

A Deep Learning Regression Model for Photonic Crystal Fiber Sensor With XAI Feature Selection and Analysis.

A Deep Learning Multi-output regression model is employed to correctly model the relationships betwe...

Classification and deep-learning-based prediction of Alzheimer disease subtypes by using genomic data.

Late-onset Alzheimer's disease (LOAD) is the most common multifactorial neurodegenerative disease am...