AIMC Topic: Humans

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Neural network and spline-based regression for the prediction of salivary hypofunction in patients undergoing radiation therapy.

Radiation oncology (London, England)
BACKGROUND: This study leverages a large retrospective cohort of head and neck cancer patients in order to develop machine learning models to predict radiation induced hyposalivation from dose-volume histograms of the parotid glands.

Automatic detection and recognition of nasopharynx gross tumour volume (GTVnx) by deep learning for nasopharyngeal cancer radiotherapy through magnetic resonance imaging.

Radiation oncology (London, England)
BACKGROUND: In this study, we propose the deep learning model-based framework to automatically delineate nasopharynx gross tumor volume (GTVnx) in MRI images.

Impact of tumor contact surface area on collecting system entry in robot-assisted partial nephrectomy: a retrospective analysis.

BMC urology
BACKGROUND: Collecting system entry in robot-assisted partial nephrectomy may occur even in cases showing a low N factor in the R.E.N.A.L nephrometry score. Therefore, in this study, we focused on the tumor contact surface area with the adjacent rena...

Data infrastructures for AI in medical imaging: a report on the experiences of five EU projects.

European radiology experimental
Artificial intelligence (AI) is transforming the field of medical imaging and has the potential to bring medicine from the era of 'sick-care' to the era of healthcare and prevention. The development of AI requires access to large, complete, and harmo...

A deep learning algorithm to predict risk of pancreatic cancer from disease trajectories.

Nature medicine
Pancreatic cancer is an aggressive disease that typically presents late with poor outcomes, indicating a pronounced need for early detection. In this study, we applied artificial intelligence methods to clinical data from 6 million patients (24,000 p...

FUTURE OF THE LANGUAGE MODELS IN HEALTHCARE: THE ROLE OF CHATGPT.

Arquivos brasileiros de cirurgia digestiva : ABCD = Brazilian archives of digestive surgery
The field of medicine has always been at the forefront of technological innovation, constantly seeking new strategies to diagnose, treat, and prevent diseases. Guidelines for clinical practice to orientate medical teams regarding diagnosis, treatment...

Muscle magnetic resonance characterization of STIM1 tubular aggregate myopathy using unsupervised learning.

PloS one
PURPOSE: Congenital myopathies are a heterogeneous group of diseases affecting the skeletal muscles and characterized by high clinical, genetic, and histological variability. Magnetic Resonance (MR) is a valuable tool for the assessment of involved m...

Deep learning-based methods for classification of microsatellite instability in endometrial cancer from HE-stained pathological images.

Journal of cancer research and clinical oncology
BACKGROUND: Microsatellite instability (MSI) is one of the essential tumor biomarkers for cancer treatment and prognosis. The presence of more significant PD-L1 expression on the surface of tumor cells in endometrial cancer with MSI suggests that MSI...

Artificial intelligence in coronary artery calcium measurement: Barriers and solutions for implementation into daily practice.

European journal of radiology
Coronary artery calcification (CAC) measurement is a valuable predictor of cardiovascular risk. However, its measurement can be time-consuming and complex, thus driving the desire for artificial intelligence (AI)-based approaches. The aim of this rev...

Robotic instruments outside the surgical field can cause problems: A case of critical bleeding during robotic distal pancreatectomy.

Asian journal of endoscopic surgery
Robotic surgery has technical advantages including high optical magnification and articulation of forceps. However, the surgical field tends to be narrow due to the high magnification, and the forceps have no tactile sensation. A case of severe intra...