AIMC Topic: Humans

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Fundamental and practical aspects of machine learning for the peak picking of biomolecular NMR spectra.

Journal of biomolecular NMR
Rapid progress in machine learning offers new opportunities for the automated analysis of multidimensional NMR spectra ranging from protein NMR to metabolomics applications. Most recently, it has been demonstrated how deep neural networks (DNN) desig...

Intuitive master device for endoscopic robots with visual-motor correspondence.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Master devices exclusively used for endoscopes with position control are being developed as an isomorphic form of endoscopes. These master devices are difficult to intuitively operate because the movement direction of the endoscopic image...

Medical lesion segmentation by combining multimodal images with modality weighted UNet.

Medical physics
PURPOSE: Automatic segmentation of medical lesions is a prerequisite for efficient clinic analysis. Segmentation algorithms for multimodal medical images have received much attention in recent years. Different strategies for multimodal combination (o...

A Single Model Deep Learning Approach for Alzheimer's Disease Diagnosis.

Neuroscience
Early and accurate diagnosis of Alzheimer's disease (AD) and its prodromal period mild cognitive impairment (MCI) is essential for the delayed disease progression and the improved quality of patients' life. The emerging computer-aided diagnostic meth...

Practical foundations of machine learning for addiction research. Part II. Workflow and use cases.

The American journal of drug and alcohol abuse
In a continuum with applied statistics, machine learning offers a wide variety of tools to explore, analyze, and understand addiction data. These tools include algorithms that can leverage useful information from data to build models; these models ca...

Understanding the surgeon's behaviour during robot-assisted surgery: protocol for the qualitative Behav'Robot study.

BMJ open
INTRODUCTION: Robot-assisted surgery is spreading worldwide, accounting for more than 1.2 million procedures in 2019. Data are sparse in the literature regarding the surgeon's mechanisms that mediate risk-taking during a procedure, especially robot-a...

Novel computer aided diagnostic models on multimodality medical images to differentiate well differentiated liposarcomas from lipomas approached by deep learning methods.

Orphanet journal of rare diseases
BACKGROUND: Deep learning methods have great potential to predict tumor characterization, such as histological diagnosis and genetic aberration. The objective of this study was to evaluate and validate the predictive performance of multimodality imag...

Training and clinical testing of artificial intelligence derived right atrial cardiovascular magnetic resonance measurements.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Right atrial (RA) area predicts mortality in patients with pulmonary hypertension, and is recommended by the European Society of Cardiology/European Respiratory Society pulmonary hypertension guidelines. The advent of deep learning may al...

Non-Invasive Measurement Using Deep Learning Algorithm Based on Multi-Source Features Fusion to Predict PD-L1 Expression and Survival in NSCLC.

Frontiers in immunology
BACKGROUND: Programmed death-ligand 1 (PD-L1) assessment of lung cancer in immunohistochemical assays was only approved diagnostic biomarker for immunotherapy. But the tumor proportion score (TPS) of PD-L1 was challenging owing to invasive sampling a...