AIMC Topic: Adult

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Interpretable artificial intelligence to optimise use of imatinib after resection in patients with localised gastrointestinal stromal tumours: an observational cohort study.

The Lancet. Oncology
BACKGROUND: Current guidelines recommend use of adjuvant imatinib therapy for many patients with gastrointestinal stromal tumours (GISTs); however, its optimal treatment duration is unknown and some patient groups do not benefit from the therapy. We ...

Prospective Randomized Study on the Use of Robot-Assisted Postoperative Visits.

Telemedicine journal and e-health : the official journal of the American Telemedicine Association
Robot-assisted visits, as part of telemedicine, can offer doctors the opportunity to take care of patients. Due to the COVID-19 pandemic, there has been an increase in telemedicine. The use of teleconsultations, for example, has found its way into t...

Glove-Net: Enhancing Grasp Classification with Multisensory Data and Deep Learning Approach.

Sensors (Basel, Switzerland)
Grasp classification is pivotal for understanding human interactions with objects, with wide-ranging applications in robotics, prosthetics, and rehabilitation. This study introduces a novel methodology utilizing a multisensory data glove to capture i...

Development and external validation of machine learning-based models to predict patients with cellulitis developing sepsis during hospitalisation.

BMJ open
OBJECTIVE: Cellulitis is the most common cause of skin-related hospitalisations, and the mortality of patients with sepsis remains high. Some stratification models have been developed, but their performance in external validation has been unsatisfact...

AI driven analysis of MRI to measure health and disease progression in FSHD.

Scientific reports
Facioscapulohumeral muscular dystrophy (FSHD) affects roughly 1 in 7500 individuals. While at the population level there is a general pattern of affected muscles, there is substantial heterogeneity in muscle expression across- and within-patients. Th...

An auto-segmented multi-time window dual-scale neural network for brain-computer interfaces based on event-related potentials.

Journal of neural engineering
Event-related potentials (ERPs) are cerebral responses to cognitive processes, also referred to as cognitive potentials. Accurately decoding ERPs can help to advance research on brain-computer interfaces (BCIs). The spatial pattern of ERP varies with...

Deep learning-enabled classification of kidney allograft rejection on whole slide histopathologic images.

Frontiers in immunology
BACKGROUND: Diagnosis of kidney transplant rejection currently relies on manual histopathological assessment, which is subjective and susceptible to inter-observer variability, leading to limited reproducibility. We aim to develop a deep learning sys...

Nursing workload: use of artificial intelligence to develop a classifier model.

Revista latino-americana de enfermagem
OBJECTIVE: to describe the development of a predictive nursing workload classifier model, using artificial intelligence.

The freedom to run: developing an autonomous robot matching the needs of visually impaired citizens to technology opportunities.

Disability and rehabilitation. Assistive technology
Visual impairment poses significant challenges in daily life, especially when navigating unfamiliar environments, resulting in inequalities and reduced quality of life. This study aimed to gain an in-depth understanding of the needs and perspectives...