Hematology

Multi-Method Diagnosis of Blood Microscopic Sample for Early Detection of Acute Lymphoblastic Leukemia Based on Deep Learning and Hybrid Techniques.

Leukemia is one of the most dangerous types of malignancies affecting the bone marrow or blood in all age groups, both in children and adults. The most dangerous and deadly type of leukemia is acute lymphoblastic leukemia (ALL). It is diagnosed by hematologists and experts in blood and bone marrow samples using a high-quality microscope with a magnifying lens. Manual diagnosis, however, is conside...

Machine Learning Techniques in Blood Pressure Management During the Acute Phase of Ischemic Stroke.

BACKGROUND AND PURPOSE: Elevated blood pressure (BP) in acute ischemic stroke is common. A raised BP is related to mortality and disability, yet excessive BP lowering can be detrimental. The optimal BP management in acute ischemic stroke remains insufficient and relies on expert consensus statements. Permissive hypertension is recommended during the first 24-h after stroke onset, yet there is ongo...

Examination of blood samples using deep learning and mobile microscopy.

BACKGROUND: Microscopic examination of human blood samples is an excellent opportunity to assess general health status and diagnose diseases. Conventi...

A prospective cohort study of the accuracy and safety of robot-assisted minimally invasive spinal surgery.

BACKGROUND: Robot-assisted open surgery (RA-OS) is now commonly used in traditional open-exposure spinal screw placement surgery. With the help of rob...

Robot-Assisted Simple Prostatectomy Endoscopic Enucleation of the Prostate: A Systematic Review and Meta-Analysis of Comparative Trials.

Robot-assisted simple prostatectomy (RASP) and endoscopic enucleation of the prostate (EEP) are two minimally invasive alternatives to simple prostat...

Usefulness of Thromboelastography for Perioperative Evaluation of Hemostatic Profile in Patients with Primary Brain Tumors Undergoing Surgery.

CONTEXT: Hemostatic abnormalities are more common in patients with brain tumors than systemic malignant diseases. Conventional coagulation tests (CCT)...

A novel bone registration method using impression molding and structured-light 3D scanning technology.

Accurate bone registration is critical for computer navigation and robotic surgery. Existing registration systems are expensive, cumbersome, limited i...

Effects of age, gender, and hemisphere on cerebrovascular hemodynamics in children and young adults: Developmental scores and machine learning classifiers.

A constant blood supply to the brain is required for mental function. Research with Doppler ultrasonography has important clinical value and burgeonin...

High Plasma Concentration of Apolipoprotein C-III Confers an Increased Risk of Cerebral Ischemic Events on Cardiovascular Patients Anticoagulated With Warfarin.

INTRODUCTION: Apolipoprotein C-III (Apo CIII) is a crucial regulator of triglyceride-rich lipoproteins (TRLs) and influences the risk of cardiovascula...

Quantitative features to assist in the diagnostic assessment of chronic lymphocytic leukemia progression.

The use of artificial intelligence methods in the image-based diagnostic assessment of hematological diseases is a growing trend in recent years. In t...

Mid-term functional outcomes of extraperitoneal robot-assisted simple prostatectomy: a single centre experience.

For large prostate volume, open simple prostatectomy (OSP) or holmium laser enucleation are the gold standard surgical treatment medical therapy failu...

Non-invasively accuracy enhanced blood glucose sensor using shallow dense neural networks with NIR monitoring and medical features.

Non-invasive and accurate method for continuous blood glucose monitoring, the self-testing of blood glucose is in quest for better diagnosis, control ...

Application of photoplethysmography signals for healthcare systems: An in-depth review.

BACKGROUND AND OBJECTIVES: Photoplethysmography (PPG) is a device that measures the amount of light absorbed by the blood vessel, blood, and tissues, ...

The transferability of the minimal invasive surgeon's skills to open surgery.

BACKGROUND: Robot-assisted laparoscopic surgery has gained popularity, which has contributed to a decrease in the number of open procedures. Hence a g...

Identification of parameters and formulation of a statistical and machine learning model to identify Babesia canis infections in dogs using available ADVIA hematology analyzer data.

BACKGROUND: Canine babesiosis is an important tick-borne disease in endemic regions. One of the relevant subspecies in Europe is Babesia canis, and it...

The Design of Adolescents' Physical Health Prediction System Based on Deep Reinforcement Learning.

According to the general recognition in the first half of the last century, hypertension was not considered a kind of disease, but was regarded as a c...

Robust Deep 3D Blood Vessel Segmentation Using Structural Priors.

Deep learning has enabled significant improvements in the accuracy of 3D blood vessel segmentation. Open challenges remain in scenarios where labeled ...

WBC-AMNet: Automatic classification of WBC images using deep feature fusion network based on focalized attention mechanism.

The recognition and classification of White Blood Cell (WBC) play a remarkable role in blood-related diseases (i.e., leukemia, infections) diagnosis. ...

Photoacoustic identification of blood authenticity based on quantum-behaved particle swarm optimized wavelet neural network.

To accurately identify the blood authenticity, a set of photoacoustic detection system was established. In experiments, five kinds of blood in total o...

Development and validation of a machine learning method to predict intraoperative red blood cell transfusions in cardiothoracic surgery.

Accurately predicting red blood cell (RBC) transfusion requirements in cardiothoracic (CT) surgery could improve blood inventory management and be use...