AIMC Topic: Humans

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A review on deep learning approaches in healthcare systems: Taxonomies, challenges, and open issues.

Journal of biomedical informatics
In the last few years, the application of Machine Learning approaches like Deep Neural Network (DNN) models have become more attractive in the healthcare system given the rising complexity of the healthcare data. Machine Learning (ML) algorithms prov...

Pre-training phenotyping classifiers.

Journal of biomedical informatics
Recent transformer-based pre-trained language models have become a de facto standard for many text classification tasks. Nevertheless, their utility in the clinical domain, where classification is often performed at encounter or patient level, is sti...

Machine learning models predict coagulopathy in spontaneous intracerebral hemorrhage patients in ER.

CNS neuroscience & therapeutics
AIMS: Coagulation abnormality is one of the primary concerns for patients with spontaneous intracerebral hemorrhage admitted to ER. Conventional laboratory indicators require hours for coagulopathy diagnosis, which brings difficulties for appropriate...

Statistical stopping criteria for automated screening in systematic reviews.

Systematic reviews
Active learning for systematic review screening promises to reduce the human effort required to identify relevant documents for a systematic review. Machines and humans work together, with humans providing training data, and the machine optimising th...

Conditional Generative Adversarial Networks Aided Motion Correction of Dynamic F-FDG PET Brain Studies.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
This work set out to develop a motion-correction approach aided by conditional generative adversarial network (cGAN) methodology that allows reliable, data-driven determination of involuntary subject motion during dynamic F-FDG brain studies. Ten he...

Robotic CSP Resection and Hysterotomy Repair.

Journal of minimally invasive gynecology
STUDY OBJECTIVE: To demonstrate a technique for the robot-assisted laparoscopic surgical management of cesarean section scar ectopic pregnancy (CSP) and hysterotomy repair.

Mitigation of ocular artifacts for EEG signal using improved earth worm optimization-based neural network and lifting wavelet transform.

Computer methods in biomechanics and biomedical engineering
An Electroencephalogram (EEG) is often tarnished by various categories of artifacts. Numerous efforts have been taken to improve its quality by eliminating the artifacts. The EEG involves the biological artifacts (ocular artifacts, ECG and EMG artifa...

Overcoming the Arduous Transition for Robotic Hepatopancreatobiliary Cases: A Multi-Procedure Learning Curve Study Utilizing CUSUM Analysis.

World journal of surgery
BACKGROUND/OBJECTIVE: Quick optimization and mastery of a new technique is an important part of procedural medicine, especially in the field of minimally invasive surgery. Complex surgeries such as robotic pancreaticoduodenectomies (RPD) and robotic ...