AIMC Topic: Humans

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An Overview of Deep Learning Methods for Left Ventricle Segmentation.

Computational intelligence and neuroscience
Cardiac health diseases are one of the key causes of death around the globe. The number of heart patients has considerably increased during the pandemic. Therefore, it is crucial to assess and analyze the medical and cardiac images. Deep learning arc...

Improved UNet Deep Learning Model for Automatic Detection of Lung Cancer Nodules.

Computational intelligence and neuroscience
Uncontrolled cell growth in the two spongy lung organs in the chest is the most prevalent kind of cancer. When cells from the lungs spread to other tissues and organs, this is referred to as metastasis. This work uses image processing, deep learning,...

Effects of Timed Frontal Plane Pelvic Moments During Overground Walking With a Mobile TPAD System.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Robotic gait training may improve overground ambulation for individuals with poor control over pelvic motion. However, there is a need for an overground gait training robotic device that allows full control of pelvic movement and synchronizes applied...

What do individuals with visual impairment need and want from a dialogue-based digital assistant?

Clinical & experimental optometry
CLINICAL SIGNIFICANCE: Optometrists are well-placed to provide helpful advice and guidance to patients with visual impairment but may not know how best to do this. The availability of a reliable and comprehensive conversational agent to which patient...

The Evolution and Application of Artificial Intelligence in Rhinology: A State of the Art Review.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
OBJECTIVE: To provide a comprehensive overview on the applications of artificial intelligence (AI) in rhinology, highlight its limitations, and propose strategies for its integration into surgical practice.

Malaria Detection Using Advanced Deep Learning Architecture.

Sensors (Basel, Switzerland)
Malaria is a life-threatening disease caused by parasites that are transmitted to humans through the bites of infected mosquitoes. The early diagnosis and treatment of malaria are crucial for reducing morbidity and mortality rates, particularly in de...

Deep Learning Denoising of Low-Dose Computed Tomography Chest Images: A Quantitative and Qualitative Image Analysis.

Journal of computer assisted tomography
PURPOSE: To assess deep learning denoised (DLD) computed tomography (CT) chest images at various low doses by both quantitative and qualitative perceptual image analysis.

Artificial Intelligence in Paediatric Tuberculosis.

Pediatric radiology
Tuberculosis (TB) continues to be a leading cause of death in children despite global efforts focused on early diagnosis and interventions to limit the spread of the disease. This challenge has been made more complex in the context of the coronavirus...

A survey of machine learning-based methods for COVID-19 medical image analysis.

Medical & biological engineering & computing
The ongoing COVID-19 pandemic caused by the SARS-CoV-2 virus has already resulted in 6.6 million deaths with more than 637 million people infected after only 30 months since the first occurrences of the disease in December 2019. Hence, rapid and accu...

Explainable deep learning model to predict invasive bacterial infection in febrile young infants: A retrospective study.

International journal of medical informatics
BACKGROUND: Machine learning models have demonstrated superior performance in predicting invasive bacterial infection (IBI) in febrile infants compared to commonly used risk stratification criteria in recent studies. However, the black-box nature of ...