AIMC Topic: Humans

Clear Filters Showing 42131 to 42140 of 95995 articles

Predicting intraoperative hypotension using deep learning with waveforms of arterial blood pressure, electroencephalogram, and electrocardiogram: Retrospective study.

PloS one
To develop deep learning models for predicting Interoperative hypotension (IOH) using waveforms from arterial blood pressure (ABP), electrocardiogram (ECG), and electroencephalogram (EEG), and to determine whether combination ABP with EEG or CG impro...

Hesitant 2-tuple fuzzy linguistic multi-criteria decision-making method based on correlation measures.

PloS one
Correlation is considered the most important factor in analyzing the data in statistics. It is used to measure the movement of two different variables linearly. The concept of correlation is well-known and used in different fields to measure the asso...

Robust Brain Age Estimation Based on sMRI via Nonlinear Age-Adaptive Ensemble Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Precise prediction on brain age is urgently needed by many biomedical areas including mental rehabilitation prognosis as well as various medicine or treatment trials. People began to realize that contrasting physical (real) age and predicted brain ag...

Contribution of an anticancer drug compounding robot in reducing the risks of manual preparation in a hospital pharmacy unit specialized in oncology.

Journal of oncology pharmacy practice : official publication of the International Society of Oncology Pharmacy Practitioners
INTRODUCTION: In the last few years, pharmaceutical technology has evolved. In the field of oncology pharmacy, robots for the preparation of anti-cancer drugs have appeared to progressively replace manual preparation. The objective of this study is t...

Deep Learning-Based Time-to-Death Prediction Model for COVID-19 Patients Using Clinical Data and Chest Radiographs.

Journal of digital imaging
Accurate estimation of mortality and time to death at admission for COVID-19 patients is important and several deep learning models have been created for this task. However, there are currently no prognostic models which use end-to-end deep learning ...

Impact of the transection plan on postoperative pancreatic fistulas occurring after robot-assisted distal pancreatectomy for nonmalignant pancreatic neoplasms.

Surgical endoscopy
OBJECTIVES: Postoperative pancreatic fistula (POPF) is the main complication of distal pancreatectomy (DP) and affects the prognosis of patients. The impact of several clinical factors mentioned in recent studies on POPF remains controversial. This s...

Healthcare data integration using machine learning: A case study evaluation with health information-seeking behavior databases.

Research in social & administrative pharmacy : RSAP
BACKGROUND: The amount of data in health care is rapidly rising, leading to multiple datasets generated for any given individual. Data integration involves mapping variables in different datasets together to form a combined dataset which can then be ...

Learning low-dose CT degradation from unpaired data with flow-based model.

Medical physics
BACKGROUND: There has been growing interest in low-dose computed tomography (LDCT) for reducing the X-ray radiation to patients. However, LDCT always suffers from complex noise in reconstructed images. Although deep learning-based methods have shown ...

Development and validation of a predictive model for peripherally inserted central catheter-related thrombosis in breast cancer patients based on artificial neural network: A prospective cohort study.

International journal of nursing studies
BACKGROUND: Peripherally inserted central catheters have been extensively applied in clinical practices. However, they are associated with an increased risk of thrombosis. To improve patient care, it is critical to timely identify patients at risk of...