AIMC Topic: Humans

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Advances in Drug Design and Development for Human Therapeutics Using Artificial Intelligence-II.

Biomolecules
Building on our 2021-2022 Special Issue, "Advances in Drug Design and Development for Human Therapeutics Using Artificial Intelligence [...].

Effect of robot for medication management on home care professionals' use of working time in older people's home care: a non-randomized controlled clinical trial.

BMC health services research
BACKGROUND: Medication management has a key role in the daily tasks of home care professionals delivered to older clients in home care. The aim of this study was to examine the effect of using a robot for medication management on home care profession...

Ensemble machine learning model trained on a new synthesized dataset generalizes well for stress prediction using wearable devices.

Journal of biomedical informatics
INTRODUCTION: Advances in wearable sensor technology have enabled the collection of biomarkers that may correlate with levels of elevated stress. While significant research has been done in this domain, specifically in using machine learning to detec...

Rapid intraoperative multi-molecular diagnosis of glioma with ultrasound radio frequency signals and deep learning.

EBioMedicine
BACKGROUND: Molecular diagnosis is crucial for biomarker-assisted glioma resection and management. However, some limitations of current molecular diagnostic techniques prevent their widespread use intraoperatively. With the unique advantages of ultra...

Achalasia phenotypes and prediction of peroral endoscopic myotomy outcomes using machine learning.

Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
OBJECTIVES: High-resolution manometry (HRM) and esophagography are used for achalasia diagnosis; however, achalasia phenotypes combining esophageal motility and morphology are unknown. Moreover, predicting treatment outcomes of peroral endoscopic myo...

Predicting incomplete occlusion of intracranial aneurysms treated with flow diverters using machine learning models.

Journal of neurosurgery
OBJECTIVE: Intracranial saccular aneurysms are vascular malformations responsible for 80% of nontraumatic brain hemorrhage. Recently, flow diverters have been used as a less invasive therapeutic alternative for surgery. However, they fail to achieve ...

Machine Learning Model with Computed Tomography Radiomics and Clinicobiochemical Characteristics Predict the Subtypes of Patients with Primary Aldosteronism.

Academic radiology
RATIONALE AND OBJECTIVES: Adrenal venous sampling (AVS) is the primary method for differentiating between primary aldosterone (PA) subtypes. The aim of study is to develop prediction models for subtyping of patients with PA using computed tomography ...

Power is Nothing Without Control: Are Artificial Intelligence Chatbots in Vascular Diseases Tested and Verified?

European journal of vascular and endovascular surgery : the official journal of the European Society for Vascular Surgery