AIMC Topic: Humans

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Automated brain tumour segmentation from multi-modality magnetic resonance imaging data based on new particle swarm optimisation segmentation method.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Segmentation of brain tumours is a complex problem in medical image processing and analysis. It is a time-consuming and error-prone task. Therefore, computer-aided detection systems need to be developed to decrease physicians' workload an...

Artificial intelligence algorithms aimed at characterizing or detecting prostate cancer on MRI: How accurate are they when tested on independent cohorts? - A systematic review.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to perform a systematic review of the literature on the diagnostic performance, in independent test cohorts, of artificial intelligence (AI)-based algorithms aimed at characterizing/detecting prostate cancer on ...

Detection of 1-OHPyr in human urine using SERS with injection under wet liquid-liquid self-assembled films of β-CD-coated gold nanoparticles and deep learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
1-Hydroxypyrene (1-OHPyr), a typical hydroxylated polycyclic aromatic hydrocarbon (OH-PAH), has been commonly regarded as a urinary biomarker for assessing human exposure and health risks of PAHs. Herein, a fast and sensitive method was developed for...

Mobile-CellNet: Automatic Segmentation of Corneal Endothelium Using an Efficient Hybrid Deep Learning Model.

Cornea
PURPOSE: The corneal endothelium, the innermost layer of the human cornea, exhibits a morphology of predominantly hexagonal cells. These endothelial cells are believed to have limited regeneration capacity, and their density decreases over time. Endo...

Robotic major and minor hepatectomy: critical appraisal of learning curve and its impact on outcomes.

Surgical endoscopy
BACKGROUND: Robotic hepatectomy has gained increasing acceptance across the US. Although the robotic approach offers significant technical advantages, it is still bound by the individual surgeon's learning curve. Proficiency in this approach should t...

Robot-assisted rehabilitation training improves knee function and daily activity ability in older adults following total knee arthroplasty.

Research in nursing & health
To evaluate the effects of robot-assisted rehabilitation training on knee function and the daily activity ability of older adults following total knee arthroplasty (TKA). Eighty-eight patients who underwent TKA were randomly assigned to a robot-assis...

Applications of Deep Learning in Endocrine Neoplasms.

Surgical pathology clinics
Machine learning methods have been growing in prominence across all areas of medicine. In pathology, recent advances in deep learning (DL) have enabled computational analysis of histological samples, aiding in diagnosis and characterization in multip...

Decentralized collaborative multi-institutional PET attenuation and scatter correction using federated deep learning.

European journal of nuclear medicine and molecular imaging
PURPOSE: Attenuation correction and scatter compensation (AC/SC) are two main steps toward quantitative PET imaging, which remain challenging in PET-only and PET/MRI systems. These can be effectively tackled via deep learning (DL) methods. However, t...

Applications of artificial intelligence in forensic sciences: Current potential benefits, limitations and perspectives.

International journal of legal medicine
In recent years, new studies based on artificial intelligence (AI) have been conducted in the forensic field, posing new challenges and demonstrating the advantages and disadvantages of using AI methodologies to solve forensic well-known problems. Sp...

Incidental auditory category learning and visuomotor sequence learning do not compete for cognitive resources.

Attention, perception & psychophysics
The environment provides multiple regularities that might be useful in guiding behavior if one was able to learn their structure. Understanding statistical learning across simultaneous regularities is important, but poorly understood. We investigate ...