AIMC Topic: Artificial Intelligence

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Pharma's Bio-AI revolution.

Drug discovery today
Drug development has become unbearably slow and expensive. A key underlying problem is the clinical prediction challenge: the inability to predict which drug candidates will be safe in the human body and for whom. Recently, a dramatic regulatory chan...

Multiclass datasets expand neural network utility: an example on ankle radiographs.

International journal of computer assisted radiology and surgery
PURPOSE: Artificial intelligence in computer vision has been increasingly adapted in clinical application since the implementation of neural networks, potentially providing incremental information beyond the mere detection of pathology. As its algori...

A novel mathematical model to generate semi-automated optimal IMRT treatment plan based on predicted 3D dose distribution and prescribed dose.

Medical physics
BACKGROUND: In recent years, with the development of artificial intelligence and deep learning techniques, it has become possible to predict the three-dimensional distribution dose (3D ) of a new patient based on the treatment plans of similar recent...

CrimeNet: Neural Structured Learning using Vision Transformer for violence detection.

Neural networks : the official journal of the International Neural Network Society
The state of the art in violence detection in videos has improved in recent years thanks to deep learning models, but it is still below 90% of average precision in the most complex datasets, which may pose a problem of frequent false alarms in video ...

Automatic segmentation of kidneys in computed tomography images using U-Net.

Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique
PURPOSE: Accurate segmentation of target volumes and organs at risk from computed tomography (CT) images is essential for treatment planning in radiation therapy. The segmentation task is often done manually making it time-consuming. Besides, it is b...

New avenues in artificial-intelligence-assisted drug discovery.

Drug discovery today
Over the past decade, the amount of biomedical data available has grown at unprecedented rates. Increased automation technology and larger data volumes have encouraged the use of machine learning (ML) or artificial intelligence (AI) techniques for mi...

[Artificial intelligence in urology-opportunities and possibilities].

Urologie (Heidelberg, Germany)
The use of artificial intelligence (AI) in urology can contribute to a significant improvement with regard to individualization of diagnostics and therapy as well as healthcare cost reduction. The potential applications and advantages of AI in medici...

Informing clinical assessment by contextualizing post-hoc explanations of risk prediction models in type-2 diabetes.

Artificial intelligence in medicine
Medical experts may use Artificial Intelligence (AI) systems with greater trust if these are supported by 'contextual explanations' that let the practitioner connect system inferences to their context of use. However, their importance in improving mo...

Chemistry42: An AI-Driven Platform for Molecular Design and Optimization.

Journal of chemical information and modeling
Chemistry42 is a software platform for small molecule design and optimization that integrates Artificial Intelligence (AI) techniques with computational and medicinal chemistry methodologies. Chemistry42 efficiently generates novel molecular structu...

Deep Learning System Outperforms Clinicians in Identifying Optic Disc Abnormalities.

Journal of neuro-ophthalmology : the official journal of the North American Neuro-Ophthalmology Society
BACKGROUND: The examination of the optic nerve head (optic disc) is mandatory in patients with headache, hypertension, or any neurological symptoms, yet it is rarely or poorly performed in general clinics. We recently developed a brain and optic nerv...