AIMC Topic: Cohort Studies

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Comparison of variable selection methods for clinical predictive modeling.

International journal of medical informatics
OBJECTIVE: Modern machine learning-based modeling methods are increasingly applied to clinical problems. One such application is in variable selection methods for predictive modeling. However, there is limited research comparing the performance of cl...

Tensor-driven extraction of developmental features from varying paediatric EEG datasets.

Journal of neural engineering
OBJECTIVE: Constant changes in developing children's brains can pose a challenge in EEG dependant technologies. Advancing signal processing methods to identify developmental differences in paediatric populations could help improve function and usabil...

Deep learning strategy for accurate carotid intima-media thickness measurement: An ultrasound study on Japanese diabetic cohort.

Computers in biology and medicine
MOTIVATION: The carotid intima-media thickness (cIMT) is an important biomarker for cardiovascular diseases and stroke monitoring. This study presents an intelligence-based, novel, robust, and clinically-strong strategy that uses a combination of dee...

Superpixel-based and boundary-sensitive convolutional neural network for automated liver segmentation.

Physics in medicine and biology
Segmentation of liver in abdominal computed tomography (CT) is an important step for radiation therapy planning of hepatocellular carcinoma. Practically, a fully automatic segmentation of liver remains challenging because of low soft tissue contrast ...

Evolution of upper limb kinematics four years after subacute robot-assisted rehabilitation in stroke patients.

The International journal of neuroscience
To assess functional status and robot-based kinematic measures four years after subacute robot-assisted rehabilitation in hemiparesis. Twenty-two patients with stroke-induced hemiparesis underwent a ≥3-month upper limb combined program of robot-ass...

Unsupervised versus Supervised Identification of Prognostic Factors in Patients with Localized Retroperitoneal Sarcoma: A Data Clustering and Mahalanobis Distance Approach.

BioMed research international
The aim of this report is to unveil specific prognostic factors for retroperitoneal sarcoma (RPS) patients by univariate and multivariate statistical techniques. A phase I-II study on localized RPS treated with high-dose ifosfamide and radiotherapy f...

Predicting lithium treatment response in bipolar patients using gender-specific gene expression biomarkers and machine learning.

F1000Research
We sought to test the hypothesis that transcriptome-level gene signatures are differentially expressed between male and female bipolar patients, prior to lithium treatment, in a patient cohort who later were clinically classified as lithium treatmen...

Contralateral Breast Cancer Event Detection Using Nature Language Processing.

AMIA ... Annual Symposium proceedings. AMIA Symposium
To facilitate the identification of contralateral breast cancer events for large cohort study, we proposed and implemented a new method based on features extracted from narrative text in progress notes and features from numbers of pathology reports f...

Leveraging Collaborative Filtering to Accelerate Rare Disease Diagnosis.

AMIA ... Annual Symposium proceedings. AMIA Symposium
In the USA, rare diseases are defined as those affecting fewer than 200,000 patients at any given time. Patients with rare diseases are frequently misdiagnosed or undiagnosed which may due to the lack of knowledge and experience of care providers. We...