AIMC Topic: Humans

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Automated machine learning optimizes and accelerates predictive modeling from COVID-19 high throughput datasets.

Scientific reports
COVID-19 outbreak brings intense pressure on healthcare systems, with an urgent demand for effective diagnostic, prognostic and therapeutic procedures. Here, we employed Automated Machine Learning (AutoML) to analyze three publicly available high thr...

neoDL: a novel neoantigen intrinsic feature-based deep learning model identifies IDH wild-type glioblastomas with the longest survival.

BMC bioinformatics
BACKGROUND: Neoantigen based personalized immune therapies achieve promising results in melanoma and lung cancer, but few neoantigen based models perform well in IDH wild-type GBM, and the association between neoantigen intrinsic features and prognos...

Evaluation of Deep Learning-Based Approaches to Segment Bowel Air Pockets and Generate Pelvic Attenuation Maps from CAIPIRINHA-Accelerated Dixon MR Images.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Attenuation correction remains a challenge in pelvic PET/MRI. In addition to the segmentation/model-based approaches, deep learning methods have shown promise in synthesizing accurate pelvic attenuation maps (μ-maps). However, these methods often mis...

Future of machine learning in paediatrics.

Archives of disease in childhood
Machine learning (ML) is a branch of artificial intelligence (AI) that enables computers to learn without being explicitly programmed, through a combination of statistics and computer science. It encompasses a variety of techniques used to analyse an...

Intermediate-term survival of robot-assisted versus open radical cystectomy for muscle-invasive and high-risk non-muscle invasive bladder cancer in The Netherlands.

Urologic oncology
BACKGROUND: Radical cystectomy with pelvic lymph node dissection is the recommended treatment in non-metastatic muscle-invasive bladder cancer (MIBC). In randomised trials, robot-assisted radical cystectomy (RARC) showed non-inferior short-term oncol...

Automated detection and segmentation of sclerotic spinal lesions on body CTs using a deep convolutional neural network.

Skeletal radiology
PURPOSE: To develop a deep convolutional neural network capable of detecting spinal sclerotic metastases on body CTs.

Predicting subclinical psychotic-like experiences on a continuum using machine learning.

NeuroImage
Previous studies applying machine learning methods to psychosis have primarily been concerned with the binary classification of chronic schizophrenia patients and healthy controls. The aim of this study was to use electroencephalographic (EEG) data a...

Reversal of thoracic sympathectomy through robot-assisted microsurgical sympathetic trunk reconstruction with sural nerve graft and additional end-to-side coaptation of the intercostal nerves: A case report.

Microsurgery
Thoracic sympathectomy to treat palmar hyperhidrosis (PH) has widely been performed. Many patients regret the surgery due to compensatory hyperhidrosis (CH), gustatory hyperhidrosis, arrhythmia, hypertension, gastrointestinal disturbances, and emotio...