Hematology

MultiCOVID: a multi modal deep learning approach for COVID-19 diagnosis.

The rapid spread of the severe acute respiratory syndrome coronavirus 2 led to a global overextension of healthcare. Both Chest X-rays (CXR) and blood test have been demonstrated to have predictive value on Coronavirus Disease 2019 (COVID-19) diagnosis on different prevalence scenarios. With the objective of improving and accelerating the diagnosis of COVID-19, a multi modal prediction algorithm (...

Color-coded laparoscopic liver resection using artificial intelligence: A preliminary study.

Tashiro and colleagues demonstrated for the first time that an artificial intelligence system can precisely identify intrahepatic vascular structures during laparoscopic liver resection in real time through color coding under bleeding and indocyanine green fluorescent imaging. The system supports real-time navigation and offers potentially safer laparoscopic or robotic liver surgery.

Deep learning methods for blood flow reconstruction in a vessel with contrast enhanced x-ray computed tomography.

The reconstruction of blood velocity in a vessel from contrast enhanced x-ray computed tomography projections is a complex inverse problem. It can be ...

White blood cell image analysis for infection detection based on virtual hexagonal trellis (VHT) by using deep learning.

White blood cells (WBCs) are an indispensable constituent of the immune system. Efficient and accurate categorization of WBC is a critical task for di...

Plasma interleukin 6 as an outcome predictor of traumatic brain injury patients.

Traumatic brain injury is one of the leading causes of death and disability in young adults. Previous studies have suggested that neuroinflammatory pr...

Temperature and haemodynamic effects of a 100 mL bolus of 20% albumin at room versus body temperature in cardiac surgery patients.

To study the temperature and haemodynamic effects of room versus body temperature 20% albumin fluid bolus therapy (FBT). Single-centre, prospective,...

Comparison of clinical efficacy of da Vinci robot-assisted lung cancer surgery with two-, three- and four-hole approaches.

Orifice reduction strategies for da Vinci robotic surgery have been a hot topic of research in recent years. We retrospectively analyzed the periopera...

A multimodal deep learning model for predicting severe hemorrhage in placenta previa.

Placenta previa causes life-threatening bleeding and accurate prediction of severe hemorrhage leads to risk stratification and optimum allocation of i...

Artificial intelligence-based diagnosis of the depth of laryngopharyngeal cancer.

OBJECTIVE: Transoral surgery (TOS) is a widely used treatment for laryngopharyngeal cancer. There are some difficult cases of setting the extent of re...

Remote Expert DVT Triaging of Novice-User Compression Sonography with AI-Guidance.

BACKGROUND: Compression ultrasonography of the leg is established for triaging proximal lower extremity deep vein thrombosis (DVT). AutoDVT, a machine...

Initial experience with the da Vinci SP robot-assisted surgical staging of endometrial cancer: a retrospective comparison with conventional laparotomy.

To compare the perioperative outcomes of surgical staging performed using conventional laparotomy (LT) or the da Vinci SP robotic system (SP) in patie...

Evaluating the Use of a Robot in a Hematological Intensive Care Unit: A Pilot Study.

The aim of the SYRIACA project was to test the capability of a social robot to perform specific tasks in healthcare settings, reducing infection risks...

Uncertainty Quantification in Estimating Blood Alcohol Concentration From Transdermal Alcohol Level With Physics-Informed Neural Networks.

We develop an approach to estimate a blood alcohol signal from a transdermal alcohol signal using physics-informed neural networks (PINNs). Specifical...

A comparative evaluation of three consecutive artificial intelligence algorithms released by Techcyte for identification of blasts and white blood cells in abnormal peripheral blood films.

INTRODUCTION: Digital pathology artificial intelligence (AI) platforms have the capacity to improve over time through "deep machine learning." We have...

Blood pressure estimation and classification using a reference signal-less photoplethysmography signal: a deep learning framework.

The markers that help to predict th function of a cardiovascular system are hemodynamic parameters like blood pressure (BP), stroke volume, heart rate...

Analysis of Prospective Genetic Indicators for Prenatal Exposure to Arsenic in Newborn Cord Blood of Using Machine Learning.

Using a machine learning methods, we aim to find biological effect biomarkers of prenatal arsenic exposure in newborn cord blood. From the Gene Expres...

Automated bone marrow cell classification through dual attention gates dense neural networks.

PURPOSE: The morphology of bone marrow cells is essential in identifying malignant hematological disorders. The automatic classification model of bone...

Diagnosis of diabetes mellitus using high frequency ultrasound and convolutional neural network.

The incidence of diabetes mellitus has been increasing, prompting the search for non-invasive diagnostic methods. Although current methods exist, thes...

Comparison of effectiveness and safety of Da Vinci robot's "3 + 1" and "4 + 1" modes of treatment for colorectal cancer.

To compare the effectiveness of the Da Vinci Surgical Robot System (DSRS) "3 + 1" and "4 + 1" models for colorectal cancer (CRC). A total of 107 patie...

Ultra-fast ultrasound blood flow velocimetry for carotid artery with deep learning.

Accurate measurement of blood flow velocity is important for the prevention and early diagnosis of atherosclerosis. However, due to the uncertainty of...