AIMC Topic: Algorithms

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Toward a stable and low-resource PLM-based medical diagnostic system via prompt tuning and MoE structure.

Scientific reports
Machine learning (ML) has been extensively involved in assistant disease diagnosis and prediction systems to emancipate the serious dependence on medical resources and improve healthcare quality. Moreover, with the booming of pre-training language mo...

Segmenting functional tissue units across human organs using community-driven development of generalizable machine learning algorithms.

Nature communications
The development of a reference atlas of the healthy human body requires automated image segmentation of major anatomical structures across multiple organs based on spatial bioimages generated from various sources with differences in sample preparatio...

Application of machine learning for risky sexual behavior interventions among factory workers in China.

Frontiers in public health
INTRODUCTION: Assessing the likelihood of engaging in high-risk sexual behavior can assist in delivering tailored educational interventions. The objective of this study was to identify the most effective algorithm and assess high-risk sexual behavior...

Comparison of the data mining and machine learning algorithms for predicting the final body weight for Romane sheep breed.

PloS one
The current study aimed to predict final body weight (weight of fourth months of age to select the future reproducers) by using birth weight, birth type, sex, suckling weight, age at suckling weight, weaning weight, age at weaning weight, and age of ...

KPCA-WRF-prediction of heart rate using deep feature fusion and machine learning classification with tuned weighted hyper-parameter.

Network (Bristol, England)
The rapid advancement of technology such as stream processing technologies, deep-learning approaches, and artificial intelligence plays a prominent and vital role, to detect heart rate using a prediction model. However, the existing methods could not...

Deep learning reconstruction CT for liver metastases: low-dose dual-energy vs standard-dose single-energy.

European radiology
OBJECTIVES: To assess image quality and liver metastasis detection of reduced-dose dual-energy CT (DECT) with deep learning image reconstruction (DLIR) compared to standard-dose single-energy CT (SECT) with DLIR or iterative reconstruction (IR).

Adaptive pinning cluster synchronization of a stochastic reaction-diffusion complex network.

Neural networks : the official journal of the International Neural Network Society
This work aims to achieve cluster synchronization of a complex network by some pinning control strategies. Firstly, the network not only is affected by the reaction-diffusion and the directed coupling phenomena, but also is disturbed by the stochasti...

Modelling biochemical oxygen demand using improved neuro-fuzzy approach by marine predators algorithm.

Environmental science and pollution research international
Biochemical oxygen demand (BOD) is one of the most important parameters used for water quality assessment. Alternative methods are essential for accurately prediction of this parameter because the traditional method in predicting the BOD is time-cons...

Predicting Free Achilles Tendon Strain From Motion Capture Data Using Artificial Intelligence.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The Achilles tendon (AT) is sensitive to mechanical loading, with appropriate strain improving tissue mechanical and material properties. Estimating free AT strain is currently possible through personalized neuromusculoskeletal (NMSK) modeling; howev...

A Weighted GraphSAGE-Based Context-Aware Approach for Big Data Access Control.

Big data
Context information is the key element to realizing dynamic access control of big data. However, existing context-aware access control (CAAC) methods do not support automatic context awareness and cannot automatically model and reason about context r...