AIMC Topic: Machine Learning

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Integrating sensor fusion with machine learning for comprehensive assessment of phenotypic traits and drought response in poplar species.

Plant biotechnology journal
Increased drought frequency and severity in a warming climate threaten the health and stability of forest ecosystems, influencing the structure and functioning of forests while having far-reaching implications for global carbon storage and climate re...

Image normalization techniques and their effect on the robustness and predictive power of breast MRI radiomics.

European journal of radiology
BACKGROUND AND PURPOSE: Radiomics analysis has emerged as a promising approach to aid in cancer diagnosis and treatment. However, radiomics research currently lacks standardization, and radiomics features can be highly dependent on acquisition and pr...

A lightweight approach to gait abnormality detection for At Home health monitoring.

Computers in biology and medicine
Gait abnormality detection is a growing application in machine learning based health assessment due to its potential in domains from clinical health reviews to at home health monitoring. This latter application is of particular use for older adults, ...

Influence pathways of noise exposure on people's negative emotions and health across different activity contexts: A neural network-based double machine learning approach.

Health & place
Noise is a major global environmental issue that raises concerns about both mental and physical health. However, few studies have investigated the mediating role of emotions in the pathways linking noise exposure to health outcomes. Additionally, man...

Machine Learning Accelerated Discovery of Covalent Organic Frameworks for Environmental and Energy Applications.

Environmental science & technology
Covalent organic frameworks (COFs) are porous crystalline materials obtained by linking organic ligands covalently. Their high surface area and adjustable pore sizes make them ideal for a range of applications, including CO capture, CH storage, gas s...

Advances in machine learning for keratoconus diagnosis.

International ophthalmology
PURPOSE: To review studies reporting the role of Machine Learning (ML) techniques in the diagnosis of keratoconus (KC) over the past decade, shedding light on recent developments while also highlighting the existing gaps between academic research and...

Multimodal machine learning for predicting perioperative safety indicators in spinal surgery.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: Machine learning (ML) algorithms can utilize the large amount of tabular data in electronic health records (EHRs) to predict perioperative safety indicators. Integrating unstructured free-text inputs via natural language processin...

Ultrastructural Morphometry of Mitochondria: Comparison Between Conventional Operator-Dependent and Artificial Intelligence (AI)-Operated Machine Learning Methods.

Microscopy research and technique
Morphometric analysis of digital images is fundamental to substantiate the visual observations with objective quantitative data suitable for statistical analysis. The recent advances in artificial intelligence (AI) have allowed the development of mac...

Interpretable machine learning reveals the importance of geography and landscape arrangement for surface water quality across China.

Water research
Elucidating the influence of land use patterns on surface water quality is crucial for effective watershed management. Despite numerous studies in individual watersheds, factors influencing water quality in diverse geographical environments are less ...

Bidirectional Semantic Consistency Guided Contrastive Embedding for Generative Zero-Shot Learning.

Neural networks : the official journal of the International Neural Network Society
Generative zero-shot learning methods synthesize features for unseen classes by learning from image features and class semantic vectors, effectively addressing bias in transferring knowledge from seen to unseen classes. However, existing methods dire...