Surveys

Machine learning and deep learning systems for automated measurement of "advanced" theory of mind: Reliability and validity in children and adolescents.

Understanding individual differences in theory of mind (ToM; the ability to attribute mental states ...

RCSB Protein Data Bank (RCSB.org): delivery of experimentally-determined PDB structures alongside one million computed structure models of proteins from artificial intelligence/machine learning.

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), founding memb...

Artificial Intelligence: its Future and Impact on Acute Medicine.

This commentary explores the potential impact of artificial intelligence (AI) in acute medicine, con...

[Literacy for Appropriate Use of Medical Big Data and Artificial Intelligence].

Recent developments have enabled daily accumulated medical information to be converted into medical ...

The Bias-Variance Tradeoff in Cognitive Science.

The bias-variance tradeoff is a theoretical concept that suggests machine learning algorithms are su...

A global gridded municipal water withdrawal estimation method using aggregated data and artificial neural network.

Municipal water withdrawal (MWW) information is of great significance for water supply planning, inc...

Detrimental Detection of Advanced Lesions With AI: False Confidence or Prevalence Bias?

Deep learning joint models for extracting entities and relations in biomedical: a survey and comparison.

The rapid development of biomedicine has produced a large number of biomedical written materials. Th...

Tackling bias in AI health datasets through the STANDING Together initiative.

Surveys Aimed at General Citizens of the US and Japan About Their Attitudes Toward Electronic Medical Data Handling - 10 Years Change, Before and After Covid-19.

OBJECTIVES: To clarify the views of the general population of two countries (US and Japan), concerni...

A survey of automated methods for biomedical text simplification.

OBJECTIVE: Plain language in medicine has long been advocated as a way to improve patient understand...

Key concepts, common pitfalls, and best practices in artificial intelligence and machine learning: focus on radiomics.

Artificial intelligence (AI) and machine learning (ML) are increasingly used in radiology research t...

Natural Language Processing and Psychosis: On the Need for Comprehensive Psychometric Evaluation.

BACKGROUND AND HYPOTHESIS: Despite decades of "proof of concept" findings supporting the use of Natu...

Survey on natural language processing in medical image analysis.

Recent advancement in natural language processing (NLP) and medical imaging empowers the wide applic...

A survey of adaptive optimal control theory.

This paper makes a survey about the recent development of optimal control based on adaptive dynamic ...

[Survey and analysis on digital construction of primary hospitals in Guizhou Province].

OBJECTIVE: To investigate the utilization status and awareness of digital hospital construction amon...

BayeshERG: a robust, reliable and interpretable deep learning model for predicting hERG channel blockers.

Unintended inhibition of the human ether-à-go-go-related gene (hERG) ion channel by small molecules ...

An ISB-consistent Denavit-Hartenberg model of the human upper limb for joint kinematics optimization: validation on synthetic and robot data during a typical rehabilitation gesture.

Several biomedical contexts such as diagnosis, rehabilitation, and ergonomics require an accurate es...

Assessing socioeconomic bias in machine learning algorithms in health care: a case study of the HOUSES index.

OBJECTIVE: Artificial intelligence (AI) models may propagate harmful biases in performance and hence...

The Pitfalls of Using Open Data to Develop Deep Learning Solutions for COVID-19 Detection in Chest X-Rays.

Since the emergence of COVID-19, deep learning models have been developed to identify COVID-19 from ...

Artificial Intelligence and Machine Learning Technologies in Cancer Care: Addressing Disparities, Bias, and Data Diversity.

Artificial intelligence (AI) and machine learning (ML) technologies have not only tremendous potenti...