AIMC Topic: Research Design

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N-Level Hierarchy-Based Optimal Control to Develop Therapeutic Strategies for Ecological Evolutionary Dynamics Systems.

IEEE transactions on neural networks and learning systems
This article mainly proposes an evolutionary algorithm and its first application to develop therapeutic strategies for ecological evolutionary dynamics systems (EEDS), obtaining the balance between tumor cells and immune cells by rationally arranging...

Concordance of randomised controlled trials for artificial intelligence interventions with the CONSORT-AI reporting guidelines.

Nature communications
The Consolidated Standards of Reporting Trials extension for Artificial Intelligence interventions (CONSORT-AI) was published in September 2020. Since its publication, several randomised controlled trials (RCTs) of AI interventions have been publishe...

Cocreating an Automated mHealth Apps Systematic Review Process With Generative AI: Design Science Research Approach.

JMIR medical education
BACKGROUND: The use of mobile devices for delivering health-related services (mobile health [mHealth]) has rapidly increased, leading to a demand for summarizing the state of the art and practice through systematic reviews. However, the systematic re...

Ensemble learning based transmission line fault classification using phasor measurement unit (PMU) data with explainable AI (XAI).

PloS one
A large volume of data is being captured through the Phasor Measurement Unit (PMU), which opens new opportunities and challenges to the study of transmission line faults. To be specific, the Phasor Measurement Unit (PMU) data represents many differen...

Exploring Transformer Model in Longitudinal Pharmacokinetic/Pharmacodynamic Analyses and Comparing with Alternative Natural Language Processing Models.

Journal of pharmaceutical sciences
There remains a substantial need for a comprehensive assessment of various natural language processing (NLP) algorithms in longitudinal pharmacokinetic/pharmacodynamic (PK/PD) modeling despite recent advances in machine learning in the space of quant...

Classification of human walking context using a single-point accelerometer.

Scientific reports
Real-world walking data offers rich insights into a person's mobility. Yet, daily life variations can alter these patterns, making the data challenging to interpret. As such, it is essential to integrate context for the extraction of meaningful infor...

Beyond integrative experiment design: Systematic experimentation guided by causal discovery AI.

The Behavioral and brain sciences
Integrative experiment design is a needed improvement over ad hoc experiments, but the specific proposed method has limitations. We urge a further break with tradition through the use of an enormous untapped resource: Decades of causal discovery arti...

ChatGPT performance in prosthodontics: Assessment of accuracy and repeatability in answer generation.

The Journal of prosthetic dentistry
STATEMENT OF PROBLEM: The artificial intelligence (AI) software program ChatGPT is based on large language models (LLMs) and is widely accessible. However, in prosthodontics, little is known about its performance in generating answers.

deepPGSegNet: MRI-based pituitary gland segmentation using deep learning.

Frontiers in endocrinology
INTRODUCTION: In clinical research on pituitary disorders, pituitary gland (PG) segmentation plays a pivotal role, which impacts the diagnosis and treatment of conditions such as endocrine dysfunctions and visual impairments. Manual segmentation, whi...

Benford's Law and distributions for better drug design.

Expert opinion on drug discovery
INTRODUCTION: Modern drug discovery incorporates various tools and data, heralding the beginning of the data-driven drug design (DD) era. The distributions of chemical and physical data used for Artificial Intelligence (AI)/Machine Learning (ML) and ...