AIMC Topic: Humans

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Patient-reported outcome measures compared to clinician reported outcomes regarding incontinence and erectile dysfunction in localized prostate carcinoma after robot assisted radical prostatectomy: Impact on management.

Urologic oncology
PURPOSE/ BACKGROUND: Patient-reported outcome measures (PROMs) are widely used after robot assisted radical prostatectomy (RARP) in order to evaluate the impact/burden of the treatment. The most bothersome side effects of RARP are urine incontinence ...

Clean visual field reconstruction in robot-assisted laparoscopic surgery based on dynamic prediction.

Computers in biology and medicine
Robot-assisted minimally invasive surgery has been broadly employed in complicated operations. However, the multiple surgical instruments may occupy a large amount of visual space in complex operations performed in narrow spaces, which affects the su...

Emotion recognition in EEG signals using deep learning methods: A review.

Computers in biology and medicine
Emotions are a critical aspect of daily life and serve a crucial role in human decision-making, planning, reasoning, and other mental states. As a result, they are considered a significant factor in human interactions. Human emotions can be identifie...

Development and validation of a deep learning-based fully automated algorithm for pre-TAVR CT assessment of the aortic valvular complex and detection of anatomical risk factors: a retrospective, multicentre study.

EBioMedicine
BACKGROUND: Pre-procedural computed tomography (CT) imaging assessment of the aortic valvular complex (AVC) is essential for the success of transcatheter aortic valve replacement (TAVR). However, pre-TAVR assessment is a time-intensive process, and t...

Mitigating underreported error in food frequency questionnaire data using a supervised machine learning method and error adjustment algorithm.

BMC medical informatics and decision making
BACKGROUND: Food frequency questionnaires (FFQs) are one of the most useful tools for studying and understanding diet-disease relationships. However, because FFQs are self-reported data, they are susceptible to response bias, social desirability bias...

Serum myosin-binding protein c levels: a new marker for exclusion of preterm birth?

Turkish journal of medical sciences
BACKGROUND/AIM: To evaluate whether there is a relationship between serum myosin-binding protein C (MyBP-C) levels measured in the first trimester and the timing of delivery, and, if a relationship is detected, the potential of this relationship in d...

SWADAPT2: benefits of a collision avoidance assistance for powered wheelchair users in driving difficulty.

Disability and rehabilitation. Assistive technology
PURPOSE: In France, tens of thousands of people use a wheelchair. Driving powered wheelchairs (PWCs) present risks for users and their families. The risk of collision in PWC driver increases with severity of disability and may reduce their independen...

Simultaneous object detection and segmentation for patient-specific markerless lung tumor tracking in simulated radiographs with deep learning.

Medical physics
BACKGROUND: Real-time tumor tracking is one motion management method to address motion-induced uncertainty. To date, fiducial markers are often required to reliably track lung tumors with X-ray imaging, which carries risks of complications and leads ...

The Hybrid Deep Learning Model for Identification of Attention-Deficit/Hyperactivity Disorder Using EEG.

Clinical EEG and neuroscience
Common misbehavior among children that prevents them from paying attention to tasks and interacting with their surroundings appropriately is attention-deficit/hyperactivity disorder (ADHD). Studies of children's behavior presently face a significant ...