AIMC Topic: Data Collection

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Benchmarking missing-values approaches for predictive models on health databases.

GigaScience Apr 15, 2022
BACKGROUND: As databases grow larger, it becomes harder to fully control their collection, and they frequently come with missing values. These large databases are well suited to train machine learning models, e.g., for forecasting or to extract bioma...
Electronic Health Records Data Collection Databases, Factual Machine Learning
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Evaluating the state of the art in missing data imputation for clinical data.

Briefings in bioinformatics Jan 17, 2022
Clinical data are increasingly being mined to derive new medical knowledge with a goal of enabling greater diagnostic precision, better-personalized therapeutic regimens, improved clinical outcomes and more efficient utilization of health-care resour...
Humans Algorithms Models, Statistical Machine Learning Data Collection Cross-Sectional Studies
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PBDiff: Neural network based program-wide diffing method for binaries.

Mathematical biosciences and engineering : MBE Jan 13, 2022
Program-wide binary code diffing is widely used in the binary analysis field, such as vulnerability detection. Mature tools, including BinDiff and TurboDiff, make program-wide diffing using rigorous comparison basis that varies across versions, optim...
Semantics Data Collection Neural Networks, Computer
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Assessing performance of artificial neural networks and re-sampling techniques for healthcare datasets.

Health informatics journal Jan 1, 2022
Re-sampling methods to solve class imbalance problems have shown to improve classification accuracy by mitigating the bias introduced by differences in class size. However, it is possible that a model which uses a specific re-sampling technique prior...
Health Facilities Data Collection ROC Curve Humans Delivery of Health Care Neural Networks, Computer
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On Algorithmic Fairness in Medical Practice.

Cambridge quarterly of healthcare ethics : CQ : the international journal of healthcare ethics committees Jan 1, 2022
The application of machine-learning technologies to medical practice promises to enhance the capabilities of healthcare professionals in the assessment, diagnosis, and treatment, of medical conditions. However, there is growing concern that algorithm...
Humans Data Collection Delivery of Health Care Social Justice Machine Learning
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Learning a Triplet Embedding Distance to Represent Gleason Patterns.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Gleason grade stratification is the main histological standard to determine the severity and progression of prostate cancer. Nonetheless, there is a high variability on disease diagnosis among expert pathologists (kappa lower than 0.44). End-to-end d...
Data Collection Prostatic Neoplasms Humans Deep Learning Neoplasm Grading Male
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Towards Data Integration for AI in Cancer Research.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Cancer research is increasing relying on data-driven methods and Artificial Intelligence (AI), to increase accuracy and efficiency in decision making. Such methods can solve a variety of clinically relevant problems in cancer diagnosis and treatment,...
Data Collection Neoplasms Artificial Intelligence Diagnostic Imaging Radiography Humans
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Mediterranean Food Image Recognition Using Deep Convolutional Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
We present a new dataset of food images that can be used to evaluate food recognition systems and dietary assessment systems. The Mediterranean Greek food -MedGRFood dataset consists of food images from the Mediterranean cuisine, and mainly from the ...
Food Neural Networks, Computer Data Collection
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Categorization of birth weight phenotypes for inclusion in genetic evaluations using a deep neural network.

Journal of animal science Mar 1, 2021
Birth weight (BW) serves as a valuable indicator of the economically relevant trait of calving ease (CE), and erroneous data collection for BW could impact genetic evaluations for CE. The objective of the current study was to evaluate the use of deep...
Animals Data Collection Models, Genetic Goals Birth Weight Phenotype Neural Networks, Computer
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Patient safety and quality improvement: Ethical principles for a regulatory approach to bias in healthcare machine learning.

Journal of the American Medical Informatics Association : JAMIA Dec 9, 2020
Accumulating evidence demonstrates the impact of bias that reflects social inequality on the performance of machine learning (ML) models in health care. Given their intended placement within healthcare decision making more broadly, ML tools require a...
Government Regulation Prejudice Artificial Intelligence Healthcare Disparities Social Determinants of Health Data Collection Quality Improvement Patient Safety Humans
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