AIMC Topic: Algorithms

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Secure and interpretable lung cancer prediction model using mapreduce private blockchain federated learning and XAI.

Scientific reports
Lung cancer continues to be one of the most widespread and deadly cancer diagnoses that affects humans worldwide. Early detection of lung cancer leads to decreased mortality rates; however, several challenges hinder the development and deployment of ...

Revolutionizing AMD detection Bi model CNNs and hybrid feature selection for automated grading.

Scientific reports
Age-related macular degeneration (AMD) is a common cause of vision loss in older adults. The automated grading of AMD from fundus images can aid in early detection and treatment. In this research, we propose a comprehensive framework that can enhance...

Predicting one-year overall survival in patients with AITL using machine learning algorithms: a multicenter study.

Scientific reports
Angioimmunoblastic T-cell lymphoma (AITL) is a life-threatening hematological malignancy. For patients with poor prognosis, especially those with expected survival less than 1 year, the benefits from traditional regimens are extremely limited. Theref...

Integrating swin transfer with attention mechanism based hybrid deep learning driven automated human activity recognition for enhanced disability assistance.

Scientific reports
The challenge of providing independent living for elderly and disabled individuals is a critical societal concern. Accurate human activity recognition (HAR) is core to allow the development of context-aware applications that involve the identificatio...

A dual attention and cross layer fusion network with a hybrid CNN and transformer architecture for medical image segmentation.

Scientific reports
Medical image segmentation is a crucial technology for disease diagnosis and treatment planning. However, current approaches face challenges in capturing global semantic dependencies and integrating cross-layer features. While Convolutional Neural Ne...

Developing highly accurate machine learning models for optimizing water quality management decisions in tilapia aquaculture.

Scientific reports
The optimization of water quality management is crucial for the success and sustainability of tilapia aquaculture. This study presents a novel approach for developing a decision-support system by comparing various machine learning models to predict o...

A generative framework for enhancing drug target interaction prediction in drug discovery.

Scientific reports
In silico drug-target interaction (DTI) prediction plays a key role in accelerating drug discovery and understanding molecular mechanisms. Traditional methods often struggle with the complexity and scale of biochemical data, thus limiting prediction ...

Prioritizing geochemical drivers of groundwater quality and health risks in coastal aquifers of Bangladesh using machine learning algorithms.

Environmental geochemistry and health
This study aims to evaluate key parameters of groundwater quality and associated health risks in three coastal aquifers of Cox's Bazar, Bangladesh, with a focus on manganese contamination and geochemical processes. A total of 288 groundwater samples ...

Prediction of Personalised Hypertension Using Machine Learning in Indonesian Population.

Journal of medical systems
This study aims to enhance individual hypertension risk prediction in Indonesia using machine learning (ML) models. The research investigates the predictive accuracy of models with and without incorporating personal hypertension history, seeking to u...

Malware detection using pre-trained transformer encoder with byte sequences.

PloS one
Ordinary users encounter various documents on the network every day, such as news articles, emails, and messages, and most are vulnerable to malicious attacks. Malicious attack methods continue to evolve, making neural network-based malware detection...