AIMC Topic: Data Collection

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Data-driven reduced-order modeling of spatiotemporal chaos with neural ordinary differential equations.

Chaos (Woodbury, N.Y.)
Dissipative partial differential equations that exhibit chaotic dynamics tend to evolve to attractors that exist on finite-dimensional manifolds. We present a data-driven reduced-order modeling method that capitalizes on this fact by finding a coordi...

Towards an Adaptive Clinical Transcription System for In-Situ Transcribing of Patient Encounter Information.

Studies in health technology and informatics
Electronic patient charts are essential for follow-up and multi-disciplinary care, but either take up an exorbitant amount of time during the patient encounter using a key-stroke entry system, or suffer from poor recall when made long after the encou...

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

GigaScience
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...

Evaluating the state of the art in missing data imputation for clinical data.

Briefings in bioinformatics
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...

PBDiff: Neural network based program-wide diffing method for binaries.

Mathematical biosciences and engineering : MBE
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...

Assessing performance of artificial neural networks and re-sampling techniques for healthcare datasets.

Health informatics journal
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...

On Algorithmic Fairness in Medical Practice.

Cambridge quarterly of healthcare ethics : CQ : the international journal of healthcare ethics committees
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...

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
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...

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
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,...

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
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 ...