AIMC Topic: Machine Learning

Clear Filters Showing 14621 to 14630 of 34417 articles

Emergence angle: Comprehensive analysis and machine learning prediction for clinical application.

Journal of prosthodontic research
PURPOSE: To analyze and compare the emergence angle (EA) using two measurement methods, conventional and modified (EA-GPT and EA-R), the EAs of all-natural teeth were evaluated and classified to derive a suitable and predictable clinically applicable...

A Flexible Ensemble Learning Method for Survival Extrapolation.

Therapeutic innovation & regulatory science
OBJECTIVES: Survival extrapolation is an important statistical concept for estimating long-term survival from short-term clinical trial data. It is widely used in health technology assessment (HTA). Survival extrapolation is often performed by fittin...

Breast tumor localization and segmentation using machine learning techniques: Overview of datasets, findings, and methods.

Computers in biology and medicine
The Global Cancer Statistics 2020 reported breast cancer (BC) as the most common diagnosis of cancer type. Therefore, early detection of such type of cancer would reduce the risk of death from it. Breast imaging techniques are one of the most frequen...

ANIMAL-SPOT enables animal-independent signal detection and classification using deep learning.

Scientific reports
Bioacoustic research spans a wide range of biological questions and applications, relying on identification of target species or smaller acoustic units, such as distinct call types. However, manually identifying the signal of interest is time-intensi...

Global output on artificial intelligence in the field of nursing: A bibliometric analysis and science mapping.

Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
PURPOSE: To analyze the AI research in the field of nursing, to explore the current situation, hot topics, and prospects of AI research in the field of nursing, and to provide a reference for researchers to carry out related studies.

Machine learning and statistical analysis for biomass torrefaction: A review.

Bioresource technology
Torrefaction is a remarkable technology in biomass-to-energy. However, biomass has several disadvantages, including hydrophilic properties, higher moisture, lower heating value, and heterogeneous properties. Many conventional approaches, such as kine...

Machine learning in fermentative biohydrogen production: Advantages, challenges, and applications.

Bioresource technology
Hydrogen can be produced in an environmentally friendly manner through biological processes using a variety of organic waste and biomass as feedstock. However, the complexity of biological processes limits their predictability and reliability, which ...

A systematic review on the state-of-the-art strategies for protein representation.

Computers in biology and medicine
The study of drug-target protein interaction is a key step in drug research. In recent years, machine learning techniques have become attractive for research, including drug research, due to their automated nature, predictive power, and expected effi...

Predicting stress, strain and deformation fields in materials and structures with graph neural networks.

Scientific reports
Developing accurate yet fast computational tools to simulate complex physical phenomena is a long-standing problem. Recent advances in machine learning have revolutionized the way simulations are approached, shifting from a purely physics- to AI-base...

Detecting defense mechanisms from Adult Attachment Interview (AAI) transcripts using machine learning.

Psychotherapy research : journal of the Society for Psychotherapy Research
OBJECTIVE: Defensive functioning (i.e., unconscious process used to manage real or perceived threats) may play a role in the development of various psychopathologies. It is typically assessed via observer rating measures, however, human coding of def...