AIMC Topic: Humans

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A difference degree test for comparing brain networks.

Human brain mapping
Recently, there has been a proliferation of methods investigating functional connectivity as a biomarker for mental disorders. Typical approaches include massive univariate testing at each edge or comparisons of network metrics to identify differing ...

Machine learning methods applied to audit of surgical outcomes after treatment for cancer of the head and neck.

The British journal of oral & maxillofacial surgery
Most surgical specialties have attempted to address concerns about unfair comparison of outcomes by "risk-adjusting" data to benchmark specialty-specific outcomes that are indicative of the quality of care. We are building on previous work in head an...

The utility of artificial intelligence in suicide risk prediction and the management of suicidal behaviors.

The Australian and New Zealand journal of psychiatry
OBJECTIVE: Suicide is a growing public health concern with a global prevalence of approximately 800,000 deaths per year. The current process of evaluating suicide risk is highly subjective, which can limit the efficacy and accuracy of prediction effo...

Nonmonotonic Plasticity: How Memory Retrieval Drives Learning.

Trends in cognitive sciences
What are the principles that govern whether neural representations move apart (differentiate) or together (integrate) as a function of learning? According to supervised learning models that are trained to predict outcomes in the world, integration sh...

A deep learning algorithm for one-step contour aware nuclei segmentation of histopathology images.

Medical & biological engineering & computing
This paper addresses the task of nuclei segmentation in high-resolution histopathology images. We propose an automatic end-to-end deep neural network algorithm for segmentation of individual nuclei. A nucleus-boundary model is introduced to predict n...

Automated 4π radiotherapy treatment planning with evolving knowledge-base.

Medical physics
PURPOSE: Non-coplanar 4π radiotherapy generalizes intensity modulated radiation therapy (IMRT) to automate beam geometry selection but requires complicated hyperparameter tuning to attain superior plan quality, which can be tedious and inconsistent. ...

Deep learning approaches using 2D and 3D convolutional neural networks for generating male pelvic synthetic computed tomography from magnetic resonance imaging.

Medical physics
PURPOSE: The improved soft tissue contrast of magnetic resonance imaging (MRI) compared to computed tomography (CT) makes it a useful imaging modality for radiotherapy treatment planning. Even when MR images are acquired for treatment planning, the s...

Diabetic retinopathy detection through novel tetragonal local octa patterns and extreme learning machines.

Artificial intelligence in medicine
Diabetic retinopathy (DR) is an eye disease that victimize the people suffering from diabetes from many years. The severe form of DR results in form of the blindness that can initially be controlled by the DR-screening oriented treatment. The effecti...

Breast Cancer Detection and Diagnosis Using Mammographic Data: Systematic Review.

Journal of medical Internet research
BACKGROUND: Machine learning (ML) has become a vital part of medical imaging research. ML methods have evolved over the years from manual seeded inputs to automatic initializations. The advancements in the field of ML have led to more intelligent and...

Data-driven modeling and prediction of blood glucose dynamics: Machine learning applications in type 1 diabetes.

Artificial intelligence in medicine
BACKGROUND: Diabetes mellitus (DM) is a metabolic disorder that causes abnormal blood glucose (BG) regulation that might result in short and long-term health complications and even death if not properly managed. Currently, there is no cure for diabet...