AIMC Topic: Algorithms

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Artificial intelligence based malignant lymphoma type prediction using enhanced super resolution image and hybrid feature extraction algorithm.

Computers in biology and medicine
In the medical field, the most common and frequent type of blood cancer is lymphoma. Accurately predicting and early response to lymphoma treatment will be useful for initiating treatment plans to achieve a greater rate of cure or reduced risk of tre...

Radiology report generation based on adaptive enhanced fusion of multi features.

Computers in biology and medicine
The radiology report is essential for doctors' diagnosis and treatment. The automatic generation of radiology reports can assist doctors in diagnosis and treatment, thereby reducing their workload. Some existing studies consider the entire radiologic...

Short-term spatial prediction of algal blooms in Lake Taihu via machine learning and GOCI observations.

Journal of environmental management
Harmful algal blooms are critical issues in eutrophic lakes worldwide. However, predicting the spatial distribution of algal blooms at the pixel level is still a challenge. In this study, floating algae cover (FAC) was used to extract algal coverage ...

Exploring best-performing radiomic features with combined multilevel discrete wavelet decompositions for multiclass COVID-19 classification using chest X-ray images.

Computers in biology and medicine
Discrete wavelet transforms have been applied in many machine learning models for the analysis of COVID-19; however, little is known about the impact of combined multilevel wavelet decompositions for the disease identification. This study proposes a ...

A combined attention mechanism for brain tumor segmentation of lower-grade glioma in magnetic resonance images.

Computers in biology and medicine
Low-grade gliomas (LGGs) are among the most problematic brain tumors to reliably segment in FLAIR MRI, and effective delineation of these lesions is critical for clinical diagnosis, treatment planning, and patient monitoring. Nevertheless, convention...

Body Weight Estimation in Holstein × Zebu Crossbred Heifers: Comparative Analysis of XGBoost and LightGBM Algorithms.

Veterinary medicine and science
This study evaluates the effectiveness of XGBoost and LightGBM algorithms for estimating the live weight of Holstein×Zebu crossbred heifers. The study compares the performance of both algorithms using a wide range of biometric measurements and tests ...

Artificial intelligence in forensic mental health: A review of applications and implications.

Journal of forensic and legal medicine
This narrative review explores the transformative role of artificial intelligence (AI) in forensic mental health, focusing on its applications, benefits, limitations, and ethical considerations. AI's capabilities, particularly in areas such as risk a...

MHS U-Net: Multi-scale hybrid subtraction network for medical image segmentation.

Computers in biology and medicine
Medical image segmentation plays a critical role in modern clinical diagnosis. However, existing methods face challenges such as insufficient feature extraction, limited spatial modeling capabilities, and restricted generalization ability with low co...

Predicting Weaning Weight of Romanov Lambs From Biometric Measurements Before Weaning Age Using Machine Learning Algorithms.

Veterinary medicine and science
BACKGROUND: Machine learning systems learn from historical data to forecast future outcomes. In the context of livestock farming, machine learning can be utilized to predict variables such as growth rates, milk production and breeding success by anal...

Self-Supervised Temperature Representation Learning for Fever Screening.

IEEE transactions on cybernetics
Utilizing thermal infrared facial imaging for fever screening in public spaces has become a common strategy to curb the spread of influenza viruses. However, it is difficult to capture larger number of faces with fever labels, which makes learning fa...