AIMC Topic: Humans
Showing 64991 to 65000 of 95995 articles
Measurement of physical activity in clinical practice using accelerometers.
Journal of internal medicine
Apr 16, 2019
Accelerometers are commonly used in clinical and epidemiological research for more detailed measures of physical activity and to target the limitations of self-report methods. Sensors are attached at the hip, wrist and thigh, and the acceleration dat...
Machine Learning to Build and Validate a Model for Radiation Pneumonitis Prediction in Patients with Non-Small Cell Lung Cancer.
Clinical cancer research : an official journal of the American Association for Cancer Research
Apr 16, 2019
PURPOSE: Radiation pneumonitis is an important adverse event in patients with non-small cell lung cancer (NSCLC) receiving thoracic radiotherapy. However, the risk of radiation pneumonitis grade ≥ 2 (RP2) has not been well predicted. This study hypot...
A machine learning approach to knee osteoarthritis phenotyping: data from the FNIH Biomarkers Consortium.
Osteoarthritis and cartilage
Apr 16, 2019
OBJECTIVE: Knee osteoarthritis (KOA) is a heterogeneous condition representing a variety of potentially distinct phenotypes. The purpose of this study was to apply innovative machine learning approaches to KOA phenotyping in order to define progressi...
Pain Measurement
Osteoarthritis, Knee
Machine Learning
Collagen Type II
Databases, Factual
Humans
Cartilage, Articular
Biomarkers
Menisci, Tibial
Female
Disease Progression
National Institutes of Health (U.S.)
Aged
Congresses as Topic
Biological Variation, Population
Severity of Illness Index
Male
United States
Middle Aged
Learning soft tissue behavior of organs for surgical navigation with convolutional neural networks.
International journal of computer assisted radiology and surgery
Apr 16, 2019
PURPOSE: In surgical navigation, pre-operative organ models are presented to surgeons during the intervention to help them in efficiently finding their target. In the case of soft tissue, these models need to be deformed and adapted to the current si...
Machine learning algorithms for the detection of spurious white blood cell differentials due to erythrocyte lysis resistance.
Journal of clinical pathology
Apr 16, 2019
AIMS: Red blood cell (RBC) lysis resistance interferes with white blood cell (WBC) count and differential; still, its detection relies on the identification of an abnormal scattergram, and this is not clearly adverted by specific flags in the Beckman...
A Roadmap for Foundational Research on Artificial Intelligence in Medical Imaging: From the 2018 NIH/RSNA/ACR/The Academy Workshop.
Radiology
Apr 16, 2019
Imaging research laboratories are rapidly creating machine learning systems that achieve expert human performance using open-source methods and tools. These artificial intelligence systems are being developed to improve medical image reconstruction, ...
Deep learning only by normal brain PET identify unheralded brain anomalies.
EBioMedicine
Apr 16, 2019
BACKGROUND: Recent deep learning models have shown remarkable accuracy for the diagnostic classification. However, they have limitations in clinical application due to the gap between the training cohorts and real-world data. We aimed to develop a mo...
Remote Control of Greenhouse Vegetable Production with Artificial Intelligence-Greenhouse Climate, Irrigation, and Crop Production.
Sensors (Basel, Switzerland)
Apr 16, 2019
The global population is increasing rapidly, together with the demand for healthy fresh food. The greenhouse industry can play an important role, but encounters difficulties finding skilled staff to manage crop production. Artificial intelligence (AI...
Machine learning and complex biological data.
Genome biology
Apr 16, 2019
Machine learning has demonstrated potential in analyzing large, complex biological data. In practice, however, biological information is required in addition to machine learning for successful application.
Estimating the Population Average Treatment Effect in Observational Studies with Choice-Based Sampling.
The international journal of biostatistics
Apr 16, 2019
We consider causal inference in observational studies with choice-based sampling, in which subject enrollment is stratified on treatment choice. Choice-based sampling has been considered mainly in the econometrics literature, but it can be useful for...
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