AIMC Topic: Retrospective Studies

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A machine-learning-based method to predict adverse events in patients with dilated cardiomyopathy and severely reduced ejection fractions.

The British journal of radiology
OBJECTIVE: Patients with dilated cardiomyopathy (DCM) and severely reduced left ventricular ejection fractions (LVEFs) are at very high risks of experiencing adverse cardiac events. A machine learning (ML) method could enable more effective risk stra...

Deep Learning for Detection of Pulmonary Metastasis on Chest Radiographs.

Radiology
Background A computer-aided detection (CAD) system may help surveillance for pulmonary metastasis at chest radiography in situations where there is limited access to CT. Purpose To evaluate whether a deep learning (DL)-based CAD system can improve di...

Accurate diagnosis of sepsis using a neural network: Pilot study using routine clinical variables.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Sepsis is a severe infection that increases mortality risk and is one if the main causes of death in intensive care units. Accurate detection is key to successful interventions, but diagnosis of sepsis is complicated becaus...

Contemporary Pure Laparoscopic Robot-Assisted Laparoscopic Radical Nephrectomy: Is the Transition Worth It?

Journal of endourology
The proportion of robotic procedures continues to rise. The literature reinforces that robotic procedures take longer and are often more costly. We compared cost and perioperative outcomes of laparoscopic radical nephrectomy (LRN) and robot-assisted...

Artificial Intelligence for Identifying the Prevention of Medication Incidents Causing Serious or Moderate Harm: An Analysis Using Incident Reporters' Views.

International journal of environmental research and public health
The purpose of this study was to describe incident reporters' views identified by artificial intelligence concerning the prevention of medication incidents that were assessed, causing serious or moderate harm to patients. The information identified t...

Machine learning-based approach for disease severity classification of carpal tunnel syndrome.

Scientific reports
Identifying the severity of carpal tunnel syndrome (CTS) is essential to providing appropriate therapeutic interventions. We developed and validated machine-learning (ML) models for classifying CTS severity. Here, 1037 CTS hands with 11 variables eac...

Predicting post-operative right ventricular failure using video-based deep learning.

Nature communications
Despite progressive improvements over the decades, the rich temporally resolved data in an echocardiogram remain underutilized. Human assessments reduce the complex patterns of cardiac wall motion, to a small list of measurements of heart function. A...

Exploring the diagnostic effectiveness for myocardial ischaemia based on CCTA myocardial texture features.

BMC cardiovascular disorders
BACKGROUND: To explore the characteristics of myocardial textures on coronary computed tomography angiography (CCTA) images in patients with coronary atherosclerotic heart disease, a classification model was established, and the diagnostic effectiven...

Perioperative adverse events and functional outcomes following open and robot-assisted prostatectomy in patients over age 70.

International journal of clinical practice
AIM: To evaluate the safety (perioperative adverse events) of robot-assisted radical prostatectomy (RARP) and functional outcomes (continence and erectile dysfunction) of open and robotic radical prostatectomy in elderly patients.