AIMC Topic: Humans

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Ensemble of neural networks for 3D position estimation in monolithic PET detectors.

Physics in medicine and biology
We propose an ensemble of multilayer feedforward neural networks to estimate the 3D position of photoelectric interactions in monolithic detectors. The ensemble is trained with data generated from optical Monte Carlo simulations only. The originality...

Formalizing video documentation of the Critical View of Safety in laparoscopic cholecystectomy: a step towards artificial intelligence assistance to improve surgical safety.

Surgical endoscopy
BACKGROUND: In laparoscopic cholecystectomy (LC), achievement of the Critical View of Safety (CVS) is commonly advocated to prevent bile duct injuries (BDI). However, BDI rates remain stable, probably due to inconsistent application or a poor underst...

Multivariate classification of schizophrenia and its familial risk based on load-dependent attentional control brain functional connectivity.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology
Patients with schizophrenia (SCZ), as well as their unaffected siblings (SIB), show functional connectivity (FC) alterations during performance of tasks involving attention. As compared with SCZ, these alterations are present in SIB to a lesser exten...

IDRiD: Diabetic Retinopathy - Segmentation and Grading Challenge.

Medical image analysis
Diabetic Retinopathy (DR) is the most common cause of avoidable vision loss, predominantly affecting the working-age population across the globe. Screening for DR, coupled with timely consultation and treatment, is a globally trusted policy to avoid ...

Probability density function based modeling of spatial feature variation in capsule endoscopy data for automatic bleeding detection.

Computers in biology and medicine
Wireless capsule endoscopy (WCE) is a video technology to inspect abnormalities, like bleeding in the gastrointestinal tract. In order to avoid a complex and long duration manual review process, automatic bleeding detection schemes are developed that...

Applying density-based outlier identifications using multiple datasets for validation of stroke clinical outcomes.

International journal of medical informatics
INTRODUCTION: Clinicians commonly use the modified Rankin Scale (mRS) and the Barthel Index (BI) to measure clinical outcome after stroke. These are potential targets in machine learning models for stroke outcome prediction. Therefore, the quality of...

Intelligent Imaging: Radiomics and Artificial Neural Networks in Heart Failure.

Journal of medical imaging and radiation sciences
BACKGROUND: Our previous work with iodine meta-iodobenzylguanidine (I-mIBG) radionuclide imaging among patients with cardiomyopathy reported limitations associated with the prognostic power of global parameters derived from planar imaging [1]. Employ...

A Multichannel Convolutional Neural Network Architecture for the Detection of the State of Mind Using Physiological Signals from Wearable Devices.

Journal of healthcare engineering
Detection of the state of mind has increasingly grown into a much favored study in recent years. After the advent of smart wearables in the market, each individual now expects to be delivered with state-of-the-art reports about his body. The most dom...

KETOS: Clinical decision support and machine learning as a service - A training and deployment platform based on Docker, OMOP-CDM, and FHIR Web Services.

PloS one
BACKGROUND AND OBJECTIVE: To take full advantage of decision support, machine learning, and patient-level prediction models, it is important that models are not only created, but also deployed in a clinical setting. The KETOS platform demonstrated in...