AI Medical Compendium Topic:
Research Design

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Clinical Evaluation of Artificial Intelligence-Enabled Interventions.

Investigative ophthalmology & visual science
Artificial intelligence (AI) health technologies are increasingly available for use in real-world care. This emerging opportunity is accompanied by a need for decision makers and practitioners across healthcare systems to evaluate the safety and effe...

Semisupervised transfer learning for evaluation of model classification performance.

Biometrics
In many modern machine learning applications, changes in covariate distributions and difficulty in acquiring outcome information have posed challenges to robust model training and evaluation. Numerous transfer learning methods have been developed to ...

Adaptive selection of the optimal strategy to improve precision and power in randomized trials.

Biometrics
Benkeser et al. demonstrate how adjustment for baseline covariates in randomized trials can meaningfully improve precision for a variety of outcome types. Their findings build on a long history, starting in 1932 with R.A. Fisher and including more re...

Treatment Prediction in the ICU Using a Partitioned, Sequential, Deep Time Series Analysis.

Studies in health technology and informatics
We have developed a time-oriented machine-learning tool to predict the binary decision of administering a medication and the quantitative decision regarding the specific dose. We evaluated our tool on the MIMIC-IV ICU database, for three common medic...

Developing Robust Clinical Text Deep Learning Models - A "Painless" Approach.

Studies in health technology and informatics
The success of deep learning in natural language processing relies on ample labelled training data. However, models in the health domain often face data inadequacy due to the high cost and difficulty of acquiring training data. Developing such models...

Design of experiments and artificial neural networks as useful tools in the optimization of analytical procedure.

Polimery w medycynie
Developing the analytical procedure requires estimating what independent variables will be tested and at what levels. There are statistical models that enable the optimization of the process. They involve statistical analysis, which indicates the cru...

Machine Learning for Biological Design.

Methods in molecular biology (Clifton, N.J.)
We briefly present machine learning approaches for designing better biological experiments. These approaches build on machine learning predictors and provide additional tools to guide scientific discovery. There are two different kinds of objectives ...

Mechanistic Model-Driven Biodesign in Mammalian Synthetic Biology.

Methods in molecular biology (Clifton, N.J.)
Mathematical modeling plays a vital role in mammalian synthetic biology by providing a framework to design and optimize design circuits and engineered bioprocesses, predict their behavior, and guide experimental design. Here, we review recent models ...

Methods for Analyzing Unknown Health Risk Based on Nature Language Process (NLP).

Studies in health technology and informatics
With the rapid spread of epidemic situation, how to quickly analyze health risk factors has become a major challenge in the current public health field. The development of natural language processing (NLP) technology allows us to quickly capture the ...

Radiologist's Guide to Evaluating Publications of Clinical Research on AI: How We Do It.

Radiology
Literacy in research studies of artificial intelligence (AI) has become an important skill for radiologists. It is required to make a proper assessment of the validity, reproducibility, and clinical applicability of AI studies. However, AI studies ar...