AIMC Topic: Algorithms

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A Hybrid 2D Gaussian Filter and Deep Learning Approach with Visualization of Class Activation for Automatic Lung and Colon Cancer Diagnosis.

Technology in cancer research & treatment
Cancer is a significant public health issue due to its high prevalence and lethality, particularly lung and colon cancers, which account for over a quarter of all cancer cases. This study aims to enhance the detection rate of lung and colon cancer by...

Towards Explainable Detection of Alzheimer's Disease: A Fusion of Deep Convolutional Neural Network and Enhanced Weighted Fuzzy C-Mean.

Current medical imaging
BACKGROUND: Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, posing a significant challenge for individuals and society. Early detection and treatment are essential for effective disease managem...

Estimating protein-ligand interactions with geometric deep learning and mixture density models.

Journal of biosciences
Understanding the interactions between a ligand and its molecular target is crucial in guiding the optimization of molecules for any drug design workflow. Multiple experimental and computational methods have been developed to better understand these...

Constructing a Classification Model for Cervical Cancer Tumor Tissue and Normal Tissue Based on CT Radiomics.

Technology in cancer research & treatment
This study aimed to develop an automated classification framework for distinguishing between cervical cancer tumor and normal uterine tissue, leveraging CT images for radiomics feature extraction. We retrospectively analyzed CT images from 117 cervic...

BoneScore: A natural language processing algorithm to extract bone mineral density data from DXA scans.

Health informatics journal
To develop and test an NLP algorithm that accurately detects the presence of information reported from DXA scans containing femoral neck T-scores of the patients scanned. A rule-based NLP algorithm that iteratively built a collection of regular exp...

Machine Learning in Pain Neuromodulation.

Advances in experimental medicine and biology
This chapter highlights the intersection of pain neuromodulation and machine learning (ML), exploring current limitations in pain management and how ML techniques can address these challenges. Neuromodulation technologies, such as spinal cord stimula...

Comprehensive Overview of Computational Modeling and Artificial Intelligence in Pediatric Neurosurgery.

Advances in experimental medicine and biology
In this chapter, we give an overview of artificial intelligence tools and their use thus far in pediatric neurosurgery. We discuss different machine learning algorithms from a data-driven approach in order to guide clinicians and scientists as they a...

Computational Modeling and AI in Radiation Neuro-Oncology and Radiosurgery.

Advances in experimental medicine and biology
The chapter explores the extensive integration of artificial intelligence (AI) in healthcare systems, with a specific focus on its application in stereotactic radiosurgery. The rapid evolution of AI technology has led to promising developments in thi...

Machine Learning and Radiomics in Gliomas.

Advances in experimental medicine and biology
The integration of machine learning (ML) and radiomics is emerging as a pivotal advancement in glioma research, offering novel insights into the diagnosis, prognosis, and treatment of these complex tumors. Radiomics involves the extraction of a multi...

Meta-transfer Learning for Brain Tumor Segmentation: Within and Beyond Glioma.

Advances in experimental medicine and biology
In recent years, numerous algorithms have emerged for the segmentation of brain tumors, propelled by both the advancements of deep learning techniques and the influential open benchmark set by the BraTS challenge. This chapter provides an overview of...