AIMC Topic: Middle Aged

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Using Machine Learning Algorithms to Predict Hepatitis B Surface Antigen Seroclearance.

Computational and mathematical methods in medicine
Hepatitis B surface antigen (HBsAg) seroclearance during treatment is associated with a better prognosis among patients with chronic hepatitis B (CHB). Significant gaps remain in our understanding on how to predict HBsAg seroclearance accurately and ...

Comparative outcomes of minimally invasive and robotic-assisted esophagectomy.

Surgical endoscopy
OBJECTIVE: Minimally invasive esophagectomy (MIE) has demonstrated superior outcomes compared to open approaches. The myriad of techniques has precluded the recommendation of a standard approach. The addition of robotics to esophageal resection has p...

Design and Implementation of a Machine Learning Based EEG Processor for Accurate Estimation of Depth of Anesthesia.

IEEE transactions on biomedical circuits and systems
Accurate monitoring of the depth of anesthesia (DoA) is essential for intraoperative and postoperative patient's health. Commercially available electroencephalograph (EEG)-based DoA monitors are recommended only for certain anesthetic drugs and speci...

Artificial neural network optimizes self-examination of osteoporosis risk in women.

The Journal of international medical research
OBJECTIVE: This study aimed to investigate the application of an artificial neural network (ANN) in optimizing the Osteoporosis Self-Assessment Tool for Asians (OSTA) score.

Robot-assisted laparoscopic augmentation ileocystoplasty and excision of an intraperitoneal mass: a case report.

The Journal of international medical research
OBJECTIVE: This case is reported to introduce an advanced surgical technique and share our experience with surgeons.

Development of machine learning algorithms for prediction of prolonged opioid prescription after surgery for lumbar disc herniation.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: Spine surgery has been identified as a risk factor for prolonged postoperative opioid use. Preoperative prediction of opioid use could improve risk stratification, shared decision-making, and patient counseling before surgery.

Fully Automated Segmentation of Lower Extremity Deep Vein Thrombosis Using Convolutional Neural Network.

BioMed research international
OBJECTIVE: Deep vein thrombosis (DVT) is a disease caused by abnormal blood clots in deep veins. Accurate segmentation of DVT is important to facilitate the diagnosis and treatment. In the current study, we proposed a fully automatic method of DVT de...

A preoperative nomogram to predict major complications after robot assisted partial nephrectomy (UroCCR-57 study).

Urologic oncology
OBJECTIVE: To generate a nomogram based on preoperative parameters to predict the occurrence of a major complication within 30-days of robotic partial nephrectomy.

On-Site Computed Tomography-Derived Fractional Flow Reserve Using a Machine-Learning Algorithm - Clinical Effectiveness in a Retrospective Multicenter Cohort.

Circulation journal : official journal of the Japanese Circulation Society
BACKGROUND: This study evaluated the diagnostic capability of on-site coronary computed tomography-derived computational fractional flow reserve (CT-FFR) determinations for detecting coronary artery disease (CAD), as assessed by invasive fractional f...

Machine learning approach for distinguishing malignant and benign lung nodules utilizing standardized perinodular parenchymal features from CT.

Medical physics
PURPOSE: Computed tomography (CT) is an effective method for detecting and characterizing lung nodules in vivo. With the growing use of chest CT, the detection frequency of lung nodules is increasing. Noninvasive methods to distinguish malignant from...