Hematology

Latest AI and machine learning research in hematology for healthcare professionals.

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Partial splenectomy in the era of minimally invasive surgery: the current laparoscopic and robotic experiences.

BACKGROUND: Partial splenectomy (PS) is a spleen-preserving technique that is applied as a result of...

Mar 2015 25740639
Image segmentation and classification of white blood cells with the extreme learning machine and the fast relevance vector machine.

White blood cells (WBCs) or leukocytes are an important part of the body's defense against infectiou...

Feb 2015 25707440
Prevalence of aspirin resistance in Asian-Indian patients with stable coronary artery disease.

OBJECTIVE: To evaluate the prevalence of pharmacological resistance to aspirin therapy by measuring ...

Jan 2015 24482126
Diabetes knowledge in young adults: associations with hemoglobin A1C.

The purpose of this study was to quantify associations between hemoglobin A1C (A1C) and diabetes kno...

Jan 2015 25603310
A novel neural-inspired learning algorithm with application to clinical risk prediction.

Clinical risk prediction - the estimation of the likelihood an individual is at risk of a disease - ...

Jan 2015 25576352
Noninvasive blood glucose sensing using near infra-red spectroscopy and artificial neural networks based on inverse delayed function model of neuron.

In this paper, a non-invasive blood glucose sensing system is presented using near infra-red(NIR) sp...

Dec 2014 25503416
A novel method of adverse event detection can accurately identify venous thromboembolisms (VTEs) from narrative electronic health record data.

BACKGROUND: Venous thromboembolisms (VTEs), which include deep vein thrombosis (DVT) and pulmonary e...

Oct 2014 25332356
Immediate repair of an incompletely transected obturator nerve during robotic-assisted pelvic lymphadenectomy.

Intraoperative injury of the obturator nerve may occur in gynecologic oncologic procedures when exte...

Sep 2014 25218992
Technology advances in hospital practices: robotics in treatment of patients.

Laparoscopic cholecystectomy is widely considered as the treatment of choice for acute cholecystitis...

Sep 2014 25782187
A Deep Learning-Based Predictive Algorithm for Metabolic Syndrome Detection in the U.S. Population

Objective To develop clinically operational, population-representative risk-score models for detecti...

Sensitive Glioma Detection and Recurrence Monitoring Using a Machine Learning Model Based on Circulating Monocytes

Background: Non-invasive diagnosis, reliable recurrence surveillance remain critical unmet needs in ...

Development and Validation of a Machine Learning Model to Predict Prognosis in Patients with Advanced Head and Neck Cancer

Importance Prognostic tools beyond staging are needed to guide treatment and counseling in head and ...

Glycemic response trajectories on metformin monotherapy in real-world diabetes care

Objectives: Diabetes affects over 500 million people globally and glycemia is inadequately managed. ...

Interpretable morphology mapping of peripheral blood leukocytes using annotation-efficient artificial intelligence

Background Peripheral blood smears (PBS) review is labor-intensive, subjective, and challenging for ...

Multi-Algorithm Machine Learning Benchmarking for Pan-Cancer Classification from Tumour-Educated Platelet RNA Sequencing

Tumour-educated platelets (TEPs) carry cancer-type-specific RNA signatures accessible through whole-...

VesselSim: learning 3D blood vessel segmentation without expert annotations

Blood vessel segmentation is a core task in medical image analysis for the care of vascular diseases...

CollectionLoRA: Collecting 50 Effects in 1 LoRA via Multi-Teacher On-Policy Distillation

Customized image editing aims to equip pre-trained diffusion models with specific visual effects usi...

AI-Driven SERS for Non-invasive and Label-Free Extracellular Vesicle Detection Across Cellular Origins in Tears and Sweat

Wearable sensing technology capable of point-of-care, continuous and non-invasive analysis of exosom...

Domain-adversarial learning predicts clinically actionable drug combination synergy in leukemia patients using bulk transcriptomics data

Deep learning has gained popularity in drug combination synergy prediction; however, DL models requi...

Opportunistic CT Attenuation Biomarkers of Anemia Are Associated With Impaired Myocardial Flow Reserve and Cardiovascular Outcomes

Background: Anemia is an established marker of cardiovascular disease severity and risk which leads ...

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