AIMC Topic: Humans

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A Deep Learning Approach for Quantifying Vocal Fold Dynamics During Connected Speech Using Laryngeal High-Speed Videoendoscopy.

Journal of speech, language, and hearing research : JSLHR
PURPOSE: Voice disorders are best assessed by examining vocal fold dynamics in connected speech. This can be achieved using flexible laryngeal high-speed videoendoscopy (HSV), which enables us to study vocal fold mechanics with high temporal details....

YOLO-LOGO: A transformer-based YOLO segmentation model for breast mass detection and segmentation in digital mammograms.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Both mass detection and segmentation in digital mammograms play a crucial role in early breast cancer detection and treatment. Furthermore, clinical experience has shown that they are the upstream tasks of pathological class...

Deep Learning for Infant Cry Recognition.

International journal of environmental research and public health
Recognizing why an infant cries is challenging as babies cannot communicate verbally with others to express their wishes or needs. This leads to difficulties for parents in identifying the needs and the health of their infants. This study used deep l...

An annotated corpus of clinical trial publications supporting schema-based relational information extraction.

Journal of biomedical semantics
BACKGROUND: The evidence-based medicine paradigm requires the ability to aggregate and compare outcomes of interventions across different trials. This can be facilitated and partially automatized by information extraction systems. In order to support...

Development of a phenotype ontology for autism spectrum disorder by natural language processing on electronic health records.

Journal of neurodevelopmental disorders
BACKGROUND: Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by restricted, repetitive behavior, and impaired social communication and interactions. However, significant challenges remain in diagnosing and subtyp...

Providing physical relief for nurses by collaborative robotics.

Scientific reports
Manual patient handling is one of the most significant challenges leading to musculoskeletal burden among healthcare workers. Traditional working techniques could be enhanced by innovations that can be individually adapted to the physical capacity of...

Diagnostic accuracy of code-free deep learning for detection and evaluation of posterior capsule opacification.

BMJ open ophthalmology
OBJECTIVE: To train and validate a code-free deep learning system (CFDLS) on classifying high-resolution digital retroillumination images of posterior capsule opacification (PCO) and to discriminate between clinically significant and non-significant ...

Munich Institute of Robotics and Machine Intelligence (MIRMI) Technical University of Munich.

Laryngo- rhino- otologie
The application of robotic and intelligent technologies in healthcare is dramatically increasing. The next generation of lightweight and tactile robots have provided a great opportunity to be used for a wide range of applications from medical examina...

Patient Benefit and Quality of Life after Robot-Assisted Head and Neck Surgery.

Laryngo- rhino- otologie
Robotic systems for head and neck surgery are at different stages of technical development and clinical application. Currently, robotic systems are predominantly used for transoral surgery of the pharynx and larynx. Robotic surgery of the neck, the t...

Znet: Deep Learning Approach for 2D MRI Brain Tumor Segmentation.

IEEE journal of translational engineering in health and medicine
BACKGROUND: Detection and segmentation of brain tumors using MR images are challenging and valuable tasks in the medical field. Early diagnosing and localizing of brain tumors can save lives and provide timely options for physicians to select efficie...