AIMC Topic: Humans

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Machine learning for psychiatry: getting doctors at the black box?

Molecular psychiatry
Recent developments in the field of machine learning have spurred high hopes for diagnostic support for psychiatric patients based on brain MRI. But while technical advances are undoubtedly remarkable, the current trajectory of mostly proof-of-concep...

Machine-learning algorithms for predicting hospital re-admissions in sickle cell disease.

British journal of haematology
Reducing preventable hospital re-admissions in Sickle Cell Disease (SCD) could potentially improve outcomes and decrease healthcare costs. In a retrospective study of electronic health records, we hypothesized Machine-Learning (ML) algorithms may out...

A 3D-2D Hybrid U-Net Convolutional Neural Network Approach to Prostate Organ Segmentation of Multiparametric MRI.

AJR. American journal of roentgenology
OBJECTIVE: Prostate cancer is the most commonly diagnosed cancer in men in the United States with more than 200,000 new cases in 2018. Multiparametric MRI (mpMRI) is increasingly used for prostate cancer evaluation. Prostate organ segmentation is an ...

Association of a Serum Protein Signature With Rheumatoid Arthritis Development.

Arthritis & rheumatology (Hoboken, N.J.)
OBJECTIVE: The pathophysiologic events that precede the onset of rheumatoid arthritis (RA) remain incompletely understood. This study was undertaken to identify changes in the serum proteome that precede the onset of RA, with the aim of providing new...

Deep-learning-assisted detection and segmentation of rib fractures from CT scans: Development and validation of FracNet.

EBioMedicine
BACKGROUND: Diagnosis of rib fractures plays an important role in identifying trauma severity. However, quickly and precisely identifying the rib fractures in a large number of CT images with increasing number of patients is a tough task, which is al...

Deep learning-based clustering robustly identified two classes of sepsis with both prognostic and predictive values.

EBioMedicine
BACKGROUND: Sepsis is a heterogenous syndrome and individualized management strategy is the key to successful treatment. Genome wide expression profiling has been utilized for identifying subclasses of sepsis, but the clinical utility of these subcla...

Artificial intelligence in musculoskeletal oncological radiology.

Radiology and oncology
BACKGROUND: Due to the rarity of primary bone tumors, precise radiologic diagnosis often requires an experienced musculoskeletal radiologist. In order to make the diagnosis more precise and to prevent the overlooking of potentially dangerous conditio...

Accelerometer-Based Human Activity Recognition for Patient Monitoring Using a Deep Neural Network.

Sensors (Basel, Switzerland)
The objective of this study was to investigate the accuracy of a Deep Neural Network (DNN) in recognizing activities typical for hospitalized patients. A data collection study was conducted with 20 healthy volunteers (10 males and 10 females, age = 4...

Deep Learning for Osteoporosis Classification Using Hip Radiographs and Patient Clinical Covariates.

Biomolecules
This study considers the use of deep learning to diagnose osteoporosis from hip radiographs, and whether adding clinical data improves diagnostic performance over the image mode alone. For objective labeling, we collected a dataset containing 1131 im...