AIMC Topic: Algorithms

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High-efficiency spatially guided learning network for lymphoblastic leukemia detection in bone marrow microscopy images.

Computers in biology and medicine
Leukemia is a hematologic tumor that proliferates in bone marrow and seriously affects the survival of patients. Early and accurate diagnosis is crucial for effective leukemia treatment. Traditional diagnostic methods rely on experts' subjective anal...

Transfer learning based deep architecture for lung cancer classification using CT image with pattern and entropy based feature set.

Scientific reports
Early detection of lung cancer, which remains one of the leading causes of death worldwide, is important for improved prognosis, and CT scanning is an important diagnostic modality. Lung cancer classification according to CT scan is challenging since...

The dosimetric impacts of ct-based deep learning autocontouring algorithm for prostate cancer radiotherapy planning dosimetric accuracy of DirectORGANS.

BMC urology
PURPOSE: In study, we aimed to dosimetrically evaluate the usability of a new generation autocontouring algorithm (DirectORGANS) that automatically identifies organs and contours them directly in the computed tomography (CT) simulator before creating...

A RF-based end-to-end Breast Cancer Prediction algorithm.

Computers in biology and medicine
Breast cancer became the primary cause of cancer-related deaths among women year by year. Early detection and accurate prediction of breast cancer play a crucial role in strengthening the quality of human life. Many scientists have concentrated on an...

Applying stacked machine learning models to guide electrochemical oxidation of antibiotics: Key parameter identification and process optimization insights.

Journal of environmental management
The continuous accumulation of antibiotics in the environment has become an increasingly concerned global environmental problem. Electrochemical advanced oxidation processes (EAOPs) have been attracted much attention in antibiotic degradation due to ...

Data-driven equation discovery reveals nonlinear reinforcement learning in humans.

Proceedings of the National Academy of Sciences of the United States of America
Computational models of reinforcement learning (RL) have significantly contributed to our understanding of human behavior and decision-making. Traditional RL models, however, often adopt a linear approach to updating reward expectations, potentially ...

A successive framework for brain tumor interpretation using Yolo variants.

Scientific reports
Accurate identification and segmentation of brain tumors in Magnetic Resonance Imaging (MRI) images are critical for timely diagnosis and treatment. MRI is frequently used to diagnose these disorders; however medical professionals find it challenging...

Classification accuracy of pain intensity induced by leg blood flow restriction during walking using machine learning based on electroencephalography.

Scientific reports
Pain assessment in clinical practice largely relies on patient-reported subjectivity. Although previous studies using fMRI and EEG have attempted objective pain evaluation, their focus has been limited to resting conditions. This study aimed to class...

Artificial intelligence-integrated video analysis of vessel area changes and instrument motion for microsurgical skill assessment.

Scientific reports
Mastering microsurgical skills is essential for neurosurgical trainees. Video-based analysis of target tissue changes and surgical instrument motion provides an objective, quantitative method for assessing microsurgical proficiency, potentially enhan...

Predicting stunting status among under five children in ethiopia using ensemblemachine learning algorithms.

Scientific reports
Childhood stunting is a persistent public health challenge in Ethiopia, significantly impacting children's physical growth, cognitive development, and overall well-being. This study overcame a key limitation in previous stunting prediction models by ...