AIMC Topic: Humans

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Supervised machine learning for automated classification of human Wharton's Jelly cells and mechanosensory hair cells.

PloS one
Tissue engineering and gene therapy strategies offer new ways to repair permanent damage to mechanosensory hair cells (MHCs) by differentiating human Wharton's Jelly cells (HWJCs). Conventionally, these strategies require the classification of each c...

Human locomotion with reinforcement learning using bioinspired reward reshaping strategies.

Medical & biological engineering & computing
Recent learning strategies such as reinforcement learning (RL) have favored the transition from applied artificial intelligence to general artificial intelligence. One of the current challenges of RL in healthcare relates to the development of a cont...

Detection of Epileptic Seizure Using Pretrained Deep Convolutional Neural Network and Transfer Learning.

European neurology
INTRODUCTION: The diagnosis of epilepsy takes a certain process, depending entirely on the attending physician. However, the human factor may cause erroneous diagnosis in the analysis of the EEG signal. In the past 2 decades, many advanced signal pro...

Development of artificial intelligence system for quality control of photo documentation in esophagogastroduodenoscopy.

Surgical endoscopy
BACKGROUND: Esophagogastroduodenoscopy (EGD) is generally a safe procedure, but adverse events often occur. This highlights the necessity of the quality control of EGD. Complete visualization and photo documentation of upper gastrointestinal (UGI) tr...

Impact of macular fluid volume fluctuations on visual acuity during anti-VEGF therapy in eyes with nAMD.

Eye (London, England)
OBJECTIVES: To study the effect of repeated retinal thickness fluctuations during the anti-VEGF therapy maintenance phase in neovascular age-related macular degeneration (nAMD).

Improved amyloid burden quantification with nonspecific estimates using deep learning.

European journal of nuclear medicine and molecular imaging
PURPOSE: Standardized uptake value ratio (SUVr) used to quantify amyloid-β burden from amyloid-PET scans can be biased by variations in the tracer's nonspecific (NS) binding caused by the presence of cerebrovascular disease (CeVD). In this work, we p...

Robotic approach for partial adrenalectomy.

Updates in surgery
Although safe and feasible, partial adrenalectomy is not a widespread procedure. Endorsement of robotic technologies and fluorescence techniques in adrenal surgery might help develop partial adrenalectomy and could avoid unnecessary total adrenalecto...

Predicting Glaucoma Development With Longitudinal Deep Learning Predictions From Fundus Photographs.

American journal of ophthalmology
PURPOSE: To assess whether longitudinal changes in a deep learning algorithm's predictions of retinal nerve fiber layer (RNFL) thickness based on fundus photographs can predict future development of glaucomatous visual field defects.