Surveys

Are medical oncologists ready for the artificial intelligence revolution? Evaluation of the opinions, knowledge, and experiences of medical oncologists about artificial intelligence technologies.

The use of artificial intelligence technologies (AIT) in medicine is increasing worldwide. In this s...

ChatGPT in medical research: challenging time ahead.

Since its launch, ChatGPT, an artificial intelligence-powered language model tool, has generated sig...

Dimensionality reduction for deep learning in infrared microscopy: a comparative computational survey.

While infrared microscopy provides molecular information at spatial resolution in a label-free manne...

A Survey of Deep Learning Techniques for Underwater Image Classification.

In recent years, there has been an enormous interest in using deep learning to classify underwater i...

Inducement factor of talent agglomeration in the manufacturing industrial sector: A survey on the readiness of Industry 4.0 adoption.

China's economy has progressed from a rapid growth phase to one of high-quality development and inno...

Bayesian Convolutional Neural Networks in Medical Imaging Classification: A Promising Solution for Deep Learning Limits in Data Scarcity Scenarios.

Deep neural networks (DNNs) have already impacted the field of medicine in data analysis, classifica...

Improving Reliability of Magnetic Localization Using Input Space Transformation.

Body motion tracking for medical applications has the potential to improve quality of life for peopl...

Humans inherit artificial intelligence biases.

Artificial intelligence recommendations are sometimes erroneous and biased. In our research, we hypo...

Accuracy and Reliability of Chatbot Responses to Physician Questions.

IMPORTANCE: Natural language processing tools, such as ChatGPT (generative pretrained transformer, h...

Algorithmic bias and research integrity; the role of nonhuman authors in shaping scientific knowledge with respect to artificial intelligence: a perspective.

Artificial intelligence technologies were developed to assist authors in bettering the organization ...

Machine Learning: A New Approach for Dose Individualization.

The application of machine learning (ML) has shown promising results in precision medicine due to it...

Theory, Measurement, and Psychometric Properties of Risk and Protective Factors for Drug Misuse Among Adolescents Living on or near the Cherokee Nation Reservation.

A team of tribe-based behavioral health specialists and university-based researchers partnered to im...

Exploring infection clinicians' perceptions of bias in Large Language Models (LLMs) like ChatGPT: A deep learning study.

Diagnosis of diabetes mellitus using high frequency ultrasound and convolutional neural network.

The incidence of diabetes mellitus has been increasing, prompting the search for non-invasive diagno...

Establish and validate the reliability of predictive models in bone mineral density by deep learning as examination tool for women.

UNLABELLED: While FRAX with BMD could be more precise in estimating the fracture risk, DL-based mode...

Automatic identification of posteroanterior cephalometric landmarks using a novel deep learning algorithm: a comparative study with human experts.

This study aimed to propose a fully automatic posteroanterior (PA) cephalometric landmark identifica...

Validity and reliability of an instrument evaluating the performance of intelligent chatbot: the Artificial Intelligence Performance Instrument (AIPI).

OBJECTIVES: To evaluate the reliability and validity of the Artificial Intelligence Performance Inst...

AI pitfalls and what not to do: mitigating bias in AI.

Various forms of artificial intelligence (AI) applications are being deployed and used in many healt...

What is the educational value and clinical utility of artificial intelligence for intraoperative and postoperative video analysis? A survey of surgeons and trainees.

INTRODUCTION: Surgical complications often occur due to lapses in judgment and decision-making. Adva...

Mitigating underreported error in food frequency questionnaire data using a supervised machine learning method and error adjustment algorithm.

BACKGROUND: Food frequency questionnaires (FFQs) are one of the most useful tools for studying and u...

Determinants of Attitude to a Humanoid Social Robot in Care for Older Adults: A Post-Interaction Study.

BACKGROUND While there is a growing body of research examining opinions on social robots in elderly ...