AI Medical Compendium Topic:
Uncertainty

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Detecting Uncertainty of Mortality Prediction Using Confident Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Early mortality prediction is an actively researched problem that has led to the development of various severity scores and machine learning (ML) models for accurate and reliable detection of mortality in severely ill patients staying in intensive ca...

Meeting the unmet needs of clinicians from AI systems showcased for cardiology with deep-learning-based ECG analysis.

Proceedings of the National Academy of Sciences of the United States of America
Despite their great promise, artificial intelligence (AI) systems have yet to become ubiquitous in the daily practice of medicine largely due to several crucial unmet needs of healthcare practitioners. These include lack of explanations in clinically...

A Belief Degree-Associated Fuzzy Multifactor Dimensionality Reduction Framework for Epistasis Detection.

Methods in molecular biology (Clifton, N.J.)
Epistasis is a challenge in prediction, classification, and suspicion of human genetic diseases. Many technologies, methods, and tools have been developed for epistasis detection. Multifactor dimensionality reduction (MDR) is the method commonly used...

Artificial Intelligence and Clinical Decision Making: The New Nature of Medical Uncertainty.

Academic medicine : journal of the Association of American Medical Colleges
Estimates in a 1989 study indicated that physicians in the United States were unable to reach a diagnosis that accounted for their patient's symptoms in up to 90% of outpatient patient encounters. Many proponents of artificial intelligence (AI) see t...

Adaptive back-stepping cancer control using Legendre polynomials.

IET systems biology
Here, a model-free controller for cancer treatment is presented. The treatment objective is to find a proper drug dosage that can reduce the population of tumour cells. Recently, some solutions have been proposed according to the control theory. In t...

Artificial Intelligence and Surgical Decision-making.

JAMA surgery
IMPORTANCE: Surgeons make complex, high-stakes decisions under time constraints and uncertainty, with significant effect on patient outcomes. This review describes the weaknesses of traditional clinical decision-support systems and proposes that arti...

[Robots for care. The ethics of measured action in the face of uncertainty].

Cuadernos de bioetica : revista oficial de la Asociacion Espanola de Bioetica y Etica Medica
Beyond the utopian or dystopian scenarios that accompany the progressive introduction of robots for care in daily environments, their use in the medical field entails controversies that require alternative forms of ethical responsibility. From this g...

Robust Optimal Design of Energy Efficient Series Elastic Actuators: Application to a Powered Prosthetic Ankle.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
Design of rehabilitation and physical assistance robots that work safely and efficiently despite uncertain operational conditions remains an important challenge. Current methods for the design of energy efficient series elastic actuators use an optim...

Artificial Intelligence and Black-Box Medical Decisions: Accuracy versus Explainability.

The Hastings Center report
Although decision-making algorithms are not new to medicine, the availability of vast stores of medical data, gains in computing power, and breakthroughs in machine learning are accelerating the pace of their development, expanding the range of quest...