AIMC Topic: Case-Control Studies

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Improvement of classification performance of Parkinson's disease using shape features for machine learning on dopamine transporter single photon emission computed tomography.

PloS one Jan 24, 2020
OBJECTIVE: To assess the classification performance between Parkinson's disease (PD) and normal control (NC) when semi-quantitative indicators and shape features obtained on dopamine transporter (DAT) single photon emission computed tomography (SPECT...
Corpus Striatum Tomography, Emission-Computed, Single-Photon Humans Case-Control Studies Machine Learning ROC Curve Databases, Factual Parkinson Disease Area Under Curve
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A Novel Deep Learning Approach with a 3D Convolutional Ladder Network for Differential Diagnosis of Idiopathic Normal Pressure Hydrocephalus and Alzheimer's Disease.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine Jan 22, 2020
PURPOSE: Idiopathic normal pressure hydrocephalus (iNPH) and Alzheimer's disease (AD) are geriatric diseases and common causes of dementia. Recently, many studies on the segmentation, disease detection, or classification of MRI using deep learning ha...
Neuroimaging Hydrocephalus, Normal Pressure Disease Progression Case-Control Studies Diagnosis, Computer-Assisted Deep Learning Imaging, Three-Dimensional Reproducibility of Results Image Processing, Computer-Assisted Aged Magnetic Resonance Imaging Humans Aged, 80 and over Diagnosis, Differential Artificial Intelligence Male Alzheimer Disease Brain Middle Aged Pattern Recognition, Automated Female
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Effect of a deep-learning computer-aided detection system on adenoma detection during colonoscopy (CADe-DB trial): a double-blind randomised study.

The lancet. Gastroenterology & hepatology Jan 22, 2020
BACKGROUND: Colonoscopy with computer-aided detection (CADe) has been shown in non-blinded trials to improve detection of colon polyps and adenomas by providing visual alarms during the procedure. We aimed to assess the effectiveness of a CADe system...
Case-Control Studies Diagnosis, Computer-Assisted Humans Deep Learning Female China Colorectal Neoplasms Early Diagnosis Incidence Adult Male Mass Screening Clinical Alarms Middle Aged Adenoma Colonoscopy Double-Blind Method Colonic Polyps Observer Variation
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Melanoma recognition by a deep learning convolutional neural network-Performance in different melanoma subtypes and localisations.

European journal of cancer (Oxford, England : 1990) Jan 20, 2020
BACKGROUND: Deep learning convolutional neural networks (CNNs) show great potential for melanoma diagnosis. Melanoma thickness at diagnosis among others depends on melanoma localisation and subtype (e.g. advanced thickness in acrolentiginous or nodul...
Retrospective Studies Female Melanoma Aged Male Middle Aged Case-Control Studies Deep Learning ROC Curve Follow-Up Studies Humans Neural Networks, Computer Prognosis
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Deep learning-based automated speech detection as a marker of social functioning in late-life depression.

Psychological medicine Jan 16, 2020
BACKGROUND: Late-life depression (LLD) is associated with poor social functioning. However, previous research uses bias-prone self-report scales to measure social functioning and a more objective measure is lacking. We tested a novel wearable device ...
Case-Control Studies Deep Learning Speech England Wearable Electronic Devices Aged, 80 and over Male Aging Depressive Disorder, Major Attention Neuropsychological Tests Social Interaction Social Adjustment Humans Female Aged
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Preliminary experience with an image-free handheld robot for total knee arthroplasty: 77 cases compared with a matched control group.

European journal of orthopaedic surgery & traumatology : orthopedie traumatologie Jan 16, 2020
BACKGROUND: Achieving an optimal limb alignment is an important factor affecting the long-term survival of total knee arthroplasty (TKA). This is the first study to look at the limb alignment and orientation of components in TKA using a novel image-f...
Radiography Surgery, Computer-Assisted Knee Joint Arthroplasty, Replacement, Knee Image Interpretation, Computer-Assisted Outcome and Process Assessment, Health Care Bone Malalignment Male Middle Aged Postoperative Complications Case-Control Studies Robotics Humans Female
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Quantification of Retinal Nerve Fibre Layer Thickness on Optical Coherence Tomography with a Deep Learning Segmentation-Free Approach.

Scientific reports Jan 15, 2020
This study describes a segmentation-free deep learning (DL) algorithm for measuring retinal nerve fibre layer (RNFL) thickness on spectral-domain optical coherence tomography (SDOCT). The study included 25,285 B-scans from 1,338 eyes of 706 subjects....
Glaucoma Algorithms Female Cross-Sectional Studies Male Humans Tomography, Optical Coherence Nerve Fibers Retinal Ganglion Cells Visual Fields Middle Aged Case-Control Studies Deep Learning Image Processing, Computer-Assisted
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Deep learning, computer-aided radiography reading for tuberculosis: a diagnostic accuracy study from a tertiary hospital in India.

Scientific reports Jan 14, 2020
In general, chest radiographs (CXR) have high sensitivity and moderate specificity for active pulmonary tuberculosis (PTB) screening when interpreted by human readers. However, they are challenging to scale due to hardware costs and the dearth of pro...
Radiography, Thoracic India Tertiary Care Centers Tuberculosis, Pulmonary Mycobacterium tuberculosis Software Retrospective Studies Female Reproducibility of Results Male Middle Aged Case-Control Studies Humans Diagnosis, Computer-Assisted Deep Learning ROC Curve
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A practical model for the identification of congenital cataracts using machine learning.

EBioMedicine Jan 3, 2020
BACKGROUND: Approximately 1 in 33 newborns is affected by congenital anomalies worldwide. We aimed to develop a practical model for identifying infants with a high risk of congenital cataracts (CCs), which is the leading cause of avoidable childhood ...
Humans Machine Learning Algorithms Female ROC Curve Area Under Curve Cataract Models, Biological Inheritance Patterns Reproducibility of Results Risk Factors Male Case-Control Studies Child, Preschool
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Application of Machine Learning for Predicting Clinically Meaningful Outcome After Arthroscopic Femoroacetabular Impingement Surgery.

The American journal of sports medicine Dec 23, 2019
BACKGROUND: Hip arthroscopy has become an important tool for surgical treatment of intra-articular hip pathology. Predictive models for clinically meaningful outcomes in patients undergoing hip arthroscopy for femoroacetabular impingement syndrome (F...
Body Mass Index Activities of Daily Living Arthroscopy Hip Joint Minimal Clinically Important Difference Femoracetabular Impingement Adult Male Middle Aged Case-Control Studies Treatment Outcome Humans Machine Learning Female Young Adult
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