AIMC Topic: Female

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Deep learning prediction of survival in patients with heart failure using chest radiographs.

The international journal of cardiovascular imaging
Heart failure (HF) is associated with high rates of morbidity and mortality. The value of deep learning survival prediction models using chest radiographs in patients with heart failure is currently unclear. The aim of our study is to develop and val...

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...

Quantitative assessment of colour fundus photography in hyperopia children based on artificial intelligence.

BMJ open ophthalmology
OBJECTIVES: This study aimed to quantitatively evaluate optic nerve head and retinal vascular parameters in children with hyperopia in relation to age and spherical equivalent refraction (SER) using artificial intelligence (AI)-based analysis of colo...

Factorized visual representations in the primate visual system and deep neural networks.

eLife
Object classification has been proposed as a principal objective of the primate ventral visual stream and has been used as an optimization target for deep neural network models (DNNs) of the visual system. However, visual brain areas represent many d...

Harnessing Artificial Intelligence to Predict Ovarian Stimulation Outcomes in In Vitro Fertilization: Scoping Review.

Journal of medical Internet research
BACKGROUND: In the realm of in vitro fertilization (IVF), artificial intelligence (AI) models serve as invaluable tools for clinicians, offering predictive insights into ovarian stimulation outcomes. Predicting and understanding a patient's response ...

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...