AIMC Topic: Female

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Automated detection of pathologic white matter alterations in Alzheimer's disease using combined diffusivity and kurtosis method.

Psychiatry research. Neuroimaging
Diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) are important diffusion MRI techniques for detecting microstructure abnormities in diseases such as Alzheimer's. The advantages of DKI over DTI have been reported generally; however,...

Analyzing interactions on combining multiple clinical guidelines.

Artificial intelligence in medicine
Accounting for patients with multiple health conditions is a complex task that requires analysing potential interactions among recommendations meant to address each condition. Although some approaches have been proposed to address this issue, importa...

Overground vs. treadmill-based robotic gait training to improve seated balance in people with motor-complete spinal cord injury: a case report.

Journal of neuroengineering and rehabilitation
BACKGROUND: Robotic overground gait training devices, such as the Ekso, require users to actively participate in triggering steps through weight-shifting movements. It remains unknown how much the trunk muscles are activated during these movements, a...

Use of a machine learning framework to predict substance use disorder treatment success.

PloS one
There are several methods for building prediction models. The wealth of currently available modeling techniques usually forces the researcher to judge, a priori, what will likely be the best method. Super learning (SL) is a methodology that facilitat...

Portable and Reconfigurable Wrist Robot Improves Hand Function for Post-Stroke Subjects.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Rehabilitation robots have become increasingly popular for stroke rehabilitation. However, the high cost of robots hampers their implementation on a large scale. This paper implements the concept of a modular and reconfigurable robot, reducing its co...

Constrained binary classification using ensemble learning: an application to cost-efficient targeted PrEP strategies.

Statistics in medicine
Binary classification problems are ubiquitous in health and social sciences. In many cases, one wishes to balance two competing optimality considerations for a binary classifier. For instance, in resource-limited settings, an human immunodeficiency v...

Epithelium-Stroma Classification via Convolutional Neural Networks and Unsupervised Domain Adaptation in Histopathological Images.

IEEE journal of biomedical and health informatics
Epithelium-stroma classification is a necessary preprocessing step in histopathological image analysis. Current deep learning based recognition methods for histology data require collection of large volumes of labeled data in order to train a new neu...

Using Artificial Intelligence to Reduce the Risk of Nonadherence in Patients on Anticoagulation Therapy.

Stroke
BACKGROUND AND PURPOSE: This study evaluated the use of an artificial intelligence platform on mobile devices in measuring and increasing medication adherence in stroke patients on anticoagulation therapy. The introduction of direct oral anticoagulan...

Classification of High-Grade Glioma into Tumor and Nontumor Components Using Support Vector Machine.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Current imaging assessment of high-grade brain tumors relies on the Response Assessment in Neuro-Oncology criteria, which measure gross volume of enhancing and nonenhancing lesions from conventional MRI sequences. These assess...

Creating an automated trigger for sepsis clinical decision support at emergency department triage using machine learning.

PloS one
OBJECTIVE: To demonstrate the incremental benefit of using free text data in addition to vital sign and demographic data to identify patients with suspected infection in the emergency department.