AIMC Topic: Algorithms

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Deep learning solutions for inverse problems in advanced biomedical image analysis on disease detection.

Scientific reports
Inverse problems in biomedical image analysis represent a significant frontier in disease detection, leveraging computational methodologies and mathematical modelling to unravel complex data embedded within medical images. These problems include dedu...

Performance of machine learning algorithms for lung cancer prediction: a comparative approach.

Scientific reports
Due to the excessive growth of PM 2.5 in aerosol, the cases of lung cancer are increasing rapidly and are most severe among other types as the highest mortality rate. In most of the cases, lung cancer is detected with least symptoms at its later stag...

Guiding questions to avoid data leakage in biological machine learning applications.

Nature methods
Machine learning methods for extracting patterns from high-dimensional data are very important in the biological sciences. However, in certain cases, real-world applications cannot confirm the reported prediction performance. One of the main reasons ...

Applying interpretable machine learning in computational biology-pitfalls, recommendations and opportunities for new developments.

Nature methods
Recent advances in machine learning have enabled the development of next-generation predictive models for complex computational biology problems, thereby spurring the use of interpretable machine learning (IML) to unveil biological insights. However,...

CMM: A CNN-MLP Model for COVID-19 Lesion Segmentation and Severity Grading.

IEEE/ACM transactions on computational biology and bioinformatics
In this paper, a CNN-MLP model (CMM) is proposed for COVID-19 lesion segmentation and severity grading in CT images. The CMM starts by lung segmentation using UNet, and then segmenting the lesion from the lung region using a multi-scale deep supervis...

Reinforced Computer-Aided Framework for Diagnosing Thyroid Cancer.

IEEE/ACM transactions on computational biology and bioinformatics
Thyroid cancer is the most pervasive disease in the endocrine system and is getting extensive attention. The most prevalent method for an early check is ultrasound examination. Traditional research mainly concentrates on promoting the performance of ...

A Parkinson's Auxiliary Diagnosis Algorithm Based on a Hyperparameter Optimization Method of Deep Learning.

IEEE/ACM transactions on computational biology and bioinformatics
Parkinson's disease is a common mental disease in the world, especially in the middle-aged and elderly groups. Today, clinical diagnosis is the main diagnostic method of Parkinson's disease, but the diagnosis results are not ideal, especially in the ...

Morphological Rule-Constrained Object Detection of Key Structures in Infant Fundus Image.

IEEE/ACM transactions on computational biology and bioinformatics
The detection of optic disc and macula is an essential step for ROP (Retinopathy of prematurity) zone segmentation and disease diagnosis. This paper aims to enhance deep learning-based object detection with domain-specific morphological rules. Based ...

Scale Mutualized Perception for Vessel Border Detection in Intravascular Ultrasound Images.

IEEE/ACM transactions on computational biology and bioinformatics
Vessel border detection in IVUS images is essential for coronary disease diagnosis. It helps to obtain the clinical indices on the inner vessel morphology to indicate the stenosis. However, the existing methods suffer the challenge of scale-dependent...

A Secure High-Order Gene Interaction Detection Algorithm Based on Deep Neural Network.

IEEE/ACM transactions on computational biology and bioinformatics
Identifying high-order Single Nucleotide Polymorphism (SNP) interactions of additive genetic model is crucial for detecting complex disease gene-type and predicting pathogenic genes of various disorders. We present a novel framework for high-order ge...