Hematology

A systemic review and meta-analysis of the effects of perioperative anticoagulant and antiplatelet therapy on bleeding complications in robot-assisted prostatectomy.

OBJECTIVE: Robot-assisted prostatectomy is commonly performed for the management of prostate cancer. The literature has noted that prostate cancer patients are often prone to increased risk for thromboembolic complications. Normally, such situations call for long-term anticoagulant/antiplatelet therapy. However, the administration of these drugs is usually contraindicated prior to surgical interve...

[Study on noninvasive blood glucose detection method using the near-infrared light based on particle swarm optimization and back propagation neural network].

Most of the existing near-infrared noninvasive blood glucose detection models focus on the relationship between near-infrared absorbance and blood glucose concentration, but do not consider the impact of human physiological state on blood glucose concentration. In order to improve the performance of prediction model, particle swarm optimization (PSO) algorithm was used to train the structure param...

[Robot-assisted laparoscopic total hysterectomy in a patient with giant uterine fibroids and complex pelvic adhesions: a case report].

We report a case of giant hysteromyoma and complex pelvic adhesion treated by robotic assisted laparoscopic total hysterectomy and bilateral salpingec...

[Deep Learning-based Risk Prediction Model for Postoperative Healthcare-associated Infections].

Objective To develop a risk prediction model combining pre/intraoperative risk factors and intraoperative vital signs for postoperative healthcare-ass...

Prediction of diagnosis and prognosis of COVID-19 disease by blood gas parameters using decision trees machine learning model: a retrospective observational study.

The coronavirus disease 2019 (COVID-19) epidemic went down in history as a pandemic caused by corona-viruses that emerged in 2019 and spread rapidly a...

Application of Combined Prediction Model Based on Core and Coritivity Theory in Continuous Blood Pressure Prediction.

BACKGROUND AND OBJECTIVE: Blood pressure is vital evidence for clinicians to predict diseases and check the curative effect of diagnosis and treatment...

Clinical insights into hematologic malignancies and comparative analysis of molecular signatures of acute myeloid leukemia in different ethnicities using an artificial intelligence offering.

Next generation sequencing generates copious amounts of genomics data, causing manual interpretation to be laborious and non-scalable while remaining ...

Predicting outcomes after trauma: Prognostic model development based on admission features through machine learning.

In an overcrowded emergency department (ED), trauma surgeons and emergency physicians need an accurate prognostic predictor for critical decision-maki...

Highly accurate differentiation of bone marrow cell morphologies using deep neural networks on a large image data set.

Biomedical applications of deep learning algorithms rely on large expert annotated data sets. The classification of bone marrow (BM) cell cytomorpholo...

A Patch-Wise Deep Learning Approach for Myocardial Blood Flow Quantification with Robustness to Noise and Nonrigid Motion.

Quantitative analysis of dynamic contrast-enhanced cardiovascular MRI (cMRI) datasets enables the assessment of myocardial blood flow (MBF) for object...

A Deep Learning Approach to Predict Blood Pressure from PPG Signals.

Blood Pressure (BP) is one of the four primary vital signs indicating the status of the body's vital (life-sustaining) functions. BP is difficult to c...

Automatic Onsets and Systolic Peaks Detection and Segmentation of Arterial Blood Pressure Waveforms using Fully Convolutional Neural Networks.

Arterial blood pressure (ABP) waveform is a common physiological signal that contains a wealth of cardiovascular information. According to the cardiac...

Predicting the Aortic Aneurysm Postoperative Risks Based on Russian Integrated Data.

This article describes the results of feature extraction from unstructured medical records and prediction of postoperative complications for patients ...

Pan-Tissue Aging Clock Genes That Have Intimate Connections with the Immune System and Age-Related Disease.

In our recent transcriptomic meta-analysis, we used random forest machine learning to accurately predict age in human blood, bone, brain, heart, and r...

[Robot-Assisted Partial Nephrectomy for Renal Cell Carcinoma Complicated by Leriche Syndrome : A Case Report].

A 71-year-old man was referred to our hospital for treatment of a 2 cm-sized right renal mass incidentally found by computed tomography (CT) and was d...

Deep learning and capsule endoscopy: automatic identification and differentiation of small bowel lesions with distinct haemorrhagic potential using a convolutional neural network.

OBJECTIVE: Capsule endoscopy (CE) is pivotal for evaluation of small bowel disease. Obscure gastrointestinal bleeding most often originates from the s...

Machine Learning for Early Lung Cancer Identification Using Routine Clinical and Laboratory Data.

Most lung cancers are diagnosed at an advanced stage. Presymptomatic identification of high-risk individuals can prompt earlier intervention and impr...

[Single-center experience of robot-assisted laparoscopic nephron-sparing surgery for giant renal hamartoma].

The clinical data of 22 patients with giant renal hamartoma in Zhejiang Provincial People's Hospital who underwent robot-assisted laparoscopic nephron...

Unsupervised flow cytometry analysis in hematological malignancies: A new paradigm.

Ever since hematopoietic cells became "events" enumerated and characterized in suspension by cell counters or flow cytometers, researchers and enginee...

Deep Learning-Based Nuclear Lobe Count Method for Differential Count of Neutrophils.

Differentiating neutrophils based on the count of nuclear lobulation is useful for diagnosing various hematological disorders, including megaloblastic...