AIMC Topic: Humans

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Dosimetry-Driven Quality Measure of Brain Pseudo Computed Tomography Generated From Deep Learning for MRI-Only Radiation Therapy Treatment Planning.

International journal of radiation oncology, biology, physics
PURPOSE: This study aims to evaluate the impact of key parameters on the pseudo computed tomography (pCT) quality generated from magnetic resonance imaging (MRI) with a 3-dimensional (3D) convolutional neural network.

A Robotic Camera Holder Controlled by Head Movements: Exploring This New Robot-Surgeon Interface.

Surgical innovation
Most robotic camera steering devices (RCSDs) require active steering by the surgeon and necessarily increase workload. Clinical experience shows that standard laparoscopic procedures can be performed safely as solo surgery aided by RCSDs. No evidenc...

Ethics Implications of the Use of Artificial Intelligence in Violence Risk Assessment.

The journal of the American Academy of Psychiatry and the Law
Artificial intelligence is rapidly transforming the landscape of medicine. Specifically, algorithms powered by deep learning are already gaining increasingly wide adoption in fields such as radiology, pathology, and preventive medicine. Forensic psyc...

Identifying drugs with disease-modifying potential in Parkinson's disease using artificial intelligence and pharmacoepidemiology.

Pharmacoepidemiology and drug safety
PURPOSE: The aim of the study was to assess the feasibility of an approach combining computational methods and pharmacoepidemiology to identify potentially disease-modifying drugs in Parkinson's disease (PD).

Applications of artificial intelligence and machine learning in respiratory medicine.

Thorax
The past 5 years have seen an explosion of interest in the use of artificial intelligence (AI) and machine learning techniques in medicine. This has been driven by the development of deep neural networks (DNNs)-complex networks residing in silico but...

Deep Learning for Classification and Localization of COVID-19 Markers in Point-of-Care Lung Ultrasound.

IEEE transactions on medical imaging
Deep learning (DL) has proved successful in medical imaging and, in the wake of the recent COVID-19 pandemic, some works have started to investigate DL-based solutions for the assisted diagnosis of lung diseases. While existing works focus on CT scan...

Short-term outcomes of robot-assisted versus conventional laparoscopic surgery for early-stage endometrial cancer: A retrospective, single-center study.

The journal of obstetrics and gynaecology research
AIM: We compared the short-term outcomes between conventional laparoscopic surgery (CLS) and robot-assisted surgery (RAS) to assess the technical feasibility of the latter for early-stage endometrial cancer.

Inspection of visible components in urine based on deep learning.

Medical physics
PURPOSE: Urinary particles are particularly important parameters in clinical urinalysis, especially for the diagnosis of nephropathy. Therefore, it is highly important to precisely detect urinary particles in the clinical setting. However, artificial...

Multiclass semantic segmentation and quantification of traumatic brain injury lesions on head CT using deep learning: an algorithm development and multicentre validation study.

The Lancet. Digital health
BACKGROUND: CT is the most common imaging modality in traumatic brain injury (TBI). However, its conventional use requires expert clinical interpretation and does not provide detailed quantitative outputs, which may have prognostic importance. We aim...