AIMC Topic: Algorithms

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Machine learning analysis of DNA methylation profiles distinguishes primary lung squamous cell carcinomas from head and neck metastases.

Science translational medicine Sep 11, 2019
Head and neck squamous cell carcinoma (HNSC) patients are at risk of suffering from both pulmonary metastases or a second squamous cell carcinoma of the lung (LUSC). Differentiating pulmonary metastases from primary lung cancers is of high clinical i...
Head and Neck Neoplasms DNA Methylation Machine Learning Algorithms Carcinoma, Squamous Cell Reproducibility of Results Cohort Studies Lung Neoplasms Humans
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Better Sensation and Dexterity for Artificial Hands.

JAMA Sep 10, 2019
Humans Algorithms Robotics Artificial Limbs Prosthesis Design
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Magnetic Resonance Fingerprinting Reconstruction Using Recurrent Neural Networks.

Studies in health technology and informatics Sep 3, 2019
Magnetic Resonance Fingerprinting (MRF) is an imaging technique acquiring unique time signals for different tissues. Although the acquisition is highly accelerated, the reconstruction time remains a problem, as the state-of-the-art template matching ...
Algorithms Databases, Genetic Magnetic Resonance Spectroscopy Neural Networks, Computer
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Analysis of machine learning algorithms as integrative tools for validation of next generation sequencing data.

European review for medical and pharmacological sciences Sep 1, 2019
OBJECTIVE: While next generation sequencing (NGS) has become the technology of choice for clinical diagnostics, most genetic laboratories still use Sanger sequencing for orthogonal confirmation of NGS results. Previous studies have shown that when th...
High-Throughput Nucleotide Sequencing Algorithms Reproducibility of Results Sequence Analysis, DNA Humans Machine Learning
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Sound source ranging using a feed-forward neural network trained with fitting-based early stopping.

The Journal of the Acoustical Society of America Sep 1, 2019
When a feed-forward neural network (FNN) is trained for acoustic source ranging in an ocean waveguide, it is difficult evaluating the FNN ranging accuracy of unlabeled test data. The label is the distance between source and receiver array. A fitting-...
Sound Neural Networks, Computer Machine Learning Algorithms Acoustics
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Clinical Data Extraction and Normalization of Cyrillic Electronic Health Records Via Deep-Learning Natural Language Processing.

JCO clinical cancer informatics Sep 1, 2019
PURPOSE: A substantial portion of medical data is unstructured. Extracting data from unstructured text presents a barrier to advancing clinical research and improving patient care. In addition, ongoing studies have been focused predominately on the E...
Neural Networks, Computer Bulgaria Algorithms Area Under Curve Electronic Health Records Medical Informatics Biomarkers, Tumor Humans Deep Learning Natural Language Processing Female Reproducibility of Results Breast Neoplasms
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Integration of machine learning and pharmacogenomic biomarkers for predicting response to antidepressant treatment: can computational intelligence be used to augment clinical assessments?

Pharmacogenomics Sep 1, 2019
Machine Learning Algorithms Biomarkers Pharmacogenetics Polymorphism, Single Nucleotide Humans Artificial Intelligence Antidepressive Agents Depressive Disorder
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A fairer way forward for AI in health care.

Nature Sep 1, 2019
Delivery of Health Care Humans Chicago Hospitals Artificial Intelligence Algorithms Healthcare Disparities
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Machine-Learning and Stochastic Tumor Growth Models for Predicting Outcomes in Patients With Advanced Non-Small-Cell Lung Cancer.

JCO clinical cancer informatics Sep 1, 2019
PURPOSE: The prediction of clinical outcomes for patients with cancer is central to precision medicine and the design of clinical trials. We developed and validated machine-learning models for three important clinical end points in patients with adva...
Kaplan-Meier Estimate Stochastic Processes Neoplasm Metastasis Molecular Targeted Therapy Randomized Controlled Trials as Topic Neoplasm Staging Models, Biological Combined Modality Therapy Tumor Burden Lung Neoplasms Treatment Outcome Carcinoma, Non-Small-Cell Lung Algorithms Prognosis Humans Machine Learning
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Prediction of Drug Approval After Phase I Clinical Trials in Oncology: RESOLVED2.

JCO clinical cancer informatics Sep 1, 2019
PURPOSE: Drug development in oncology currently is facing a conjunction of an increasing number of antineoplastic agents (ANAs) candidate for phase I clinical trials (P1CTs) and an important attrition rate for final approval. We aimed to develop a ma...
Humans Antineoplastic Agents United States United States Food and Drug Administration Machine Learning Algorithms Reproducibility of Results Drug Approval Clinical Trials, Phase I as Topic Medical Oncology Medical Informatics
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