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Transfer learning on T1-weighted images for brain age estimation.

Mathematical biosciences and engineering : MBE
Due to both the hidden nature and the irreversibility of Alzheimers disease (AD), it has become the killer of the elderly and is thus the focus of much attention in the medical field. Radiologists compare the predicted brain age with the ground truth...

Connectome-based individualized prediction of loneliness.

Social cognitive and affective neuroscience
Loneliness is an increasingly prevalent condition linking with enhanced morbidity and premature mortality. Despite recent proposal on medicalization of loneliness, so far no effort has been made to establish a model capable of predicting loneliness a...

Robot-assisted locomotor training did not improve walking function in patients with chronic incomplete spinal cord injury: A randomized clinical trial.

Journal of rehabilitation medicine
OBJECTIVE: To assess the effects of robot-assisted locomotor training in patients with chronic incomplete spinal cord injury.

Improved Interpretability of Machine Learning Model Using Unsupervised Clustering: Predicting Time to First Treatment in Chronic Lymphocytic Leukemia.

JCO clinical cancer informatics
PURPOSE: Time to event is an important aspect of clinical decision making. This is particularly true when diseases have highly heterogeneous presentations and prognoses, as in chronic lymphocytic lymphoma (CLL). Although machine learning methods can ...

Using Machine Learning Applied to Real-World Healthcare Data for Predictive Analytics: An Applied Example in Bariatric Surgery.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
OBJECTIVES: Laparoscopic metabolic surgery (MxS) can lead to remission of type 2 diabetes (T2D); however, treatment response to MxS can be heterogeneous. Here, we demonstrate an open-source predictive analytics platform that applies machine-learning ...

Exploring the survival prognosis of lung adenocarcinoma based on the cancer genome atlas database using artificial neural network.

Medicine
The aim of this study was to investigate the clinical factors affecting the survival prognosis of lung adenocarcinoma, and to establish a predictive model of survival prognosis of lung adenocarcinoma by artificial neural network.Download the cancer g...

Artificial intelligence at the intersection of pathology and radiology in prostate cancer.

Diagnostic and interventional radiology (Ankara, Turkey)
Pathologic grading plays a key role in prostate cancer risk stratification and treatment selection, traditionally assessed from systemic core needle biopsies sampled throughout the prostate gland. Multiparametric magnetic resonance imaging (mpMRI) ha...

Semi-supervised learning of a nonnative phonetic contrast: How much feedback is enough?

Attention, perception & psychophysics
Semi-supervised learning refers to learning that occurs when feedback about performance is provided on only a subset of training trials. Algorithms for semi-supervised learning are popular in machine learning because of their minimal reliance on labe...

Validity of Natural Language Processing for Ascertainment of and Test Results in SEER Cases of Stage IV Non-Small-Cell Lung Cancer.

JCO clinical cancer informatics
PURPOSE: SEER registries do not report results of epidermal growth factor receptor () and anaplastic lymphoma kinase () mutation tests. To facilitate population-based research in molecularly defined subgroups of non-small-cell lung cancer (NSCLC), we...

Machine learning-based preoperative predictive analytics for lumbar spinal stenosis.

Neurosurgical focus
OBJECTIVEPatient-reported outcome measures (PROMs) following decompression surgery for lumbar spinal stenosis (LSS) demonstrate considerable heterogeneity. Individualized prediction tools can provide valuable insights for shared decision-making. The ...