AIMC Topic: Feasibility Studies
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Intelligent ICU for Autonomous Patient Monitoring Using Pervasive Sensing and Deep Learning.
Scientific reports
May 29, 2019
Currently, many critical care indices are not captured automatically at a granular level, rather are repetitively assessed by overburdened nurses. In this pilot study, we examined the feasibility of using pervasive sensing technology and artificial i...
Deep transfer learning methods for colon cancer classification in confocal laser microscopy images.
International journal of computer assisted radiology and surgery
May 25, 2019
PURPOSE: The gold standard for colorectal cancer metastases detection in the peritoneum is histological evaluation of a removed tissue sample. For feedback during interventions, real-time in vivo imaging with confocal laser microscopy has been propos...
Model-free prostate cancer segmentation from dynamic contrast-enhanced MRI with recurrent convolutional networks: A feasibility study.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
May 19, 2019
Dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) is a method of temporal imaging that is commonly used to aid in prostate cancer (PCa) diagnosis and staging. Typically, machine learning models designed for the segmentation and detecti...
Machine-learned target volume delineation of F-FDG PET images after one cycle of induction chemotherapy.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
May 3, 2019
Biological tumour volume (GTV) delineation on F-FDG PET acquired during induction chemotherapy (ICT) is challenging due to the reduced metabolic uptake and volume of the GTV. Automatic segmentation algorithms applied to F-FDG PET (PET-AS) imaging hav...
Can we reduce the workload of mammographic screening by automatic identification of normal exams with artificial intelligence? A feasibility study.
European radiology
Apr 16, 2019
PURPOSE: To study the feasibility of automatically identifying normal digital mammography (DM) exams with artificial intelligence (AI) to reduce the breast cancer screening reading workload.
Machine Learning for Diagnosis of Hematologic Diseases in Magnetic Resonance Imaging of Lumbar Spines.
Scientific reports
Apr 15, 2019
We aimed to assess feasibility of a support vector machine (SVM) texture classifier to discriminate pathologic infiltration patterns from the normal bone marrows in MRI. This retrospective study included 467 cases, which were split into a training (n...
Design feasibility of an automated, machine-learning based feedback system for motivational interviewing.
Psychotherapy (Chicago, Ill.)
Apr 8, 2019
Direct observation of psychotherapy and providing performance-based feedback is the gold-standard approach for training psychotherapists. At present, this requires experts and training human coding teams, which is slow, expensive, and labor intensive...
Application of a deep learning algorithm for detection and visualization of hip fractures on plain pelvic radiographs.
European radiology
Apr 1, 2019
OBJECTIVE: To identify the feasibility of using a deep convolutional neural network (DCNN) for the detection and localization of hip fractures on plain frontal pelvic radiographs (PXRs). Hip fracture is a leading worldwide health problem for the elde...
False Negative Reactions
Radiography, Abdominal
Female
Adult
Aged
Sensitivity and Specificity
Aged, 80 and over
Male
Young Adult
Middle Aged
Humans
Radiographic Image Interpretation, Computer-Assisted
Neural Networks, Computer
Feasibility Studies
Algorithms
Deep Learning
Hip Fractures
Prognosis
ROC Curve
LUADpp: an effective prediction model on prognosis of lung adenocarcinomas based on somatic mutational features.
BMC cancer
Mar 22, 2019
BACKGROUND: Lung adenocarcinoma is the most common type of lung cancers. Whole-genome sequencing studies disclosed the genomic landscape of lung adenocarcinomas. however, it remains unclear if the genetic alternations could guide prognosis prediction...
Sleep staging from single-channel EEG with multi-scale feature and contextual information.
Sleep & breathing = Schlaf & Atmung
Mar 12, 2019
PURPOSE: Portable sleep monitoring devices with less-attached sensors and high-accuracy sleep staging methods can expedite sleep disorder diagnosis. The aim of this study was to propose a single-channel EEG sleep staging model, SleepStageNet, which e...
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