AIMC Topic: Algorithms

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Multi channel fusion diffusion models for brain tumor MRI data augmentation.

Scientific reports
The early diagnosis of brain tumors is crucial for patient prognosis, and medical imaging techniques such as MRI and CT scans are essential tools for diagnosing brain tumors. However, high-quality medical image data for brain tumors is often scarce a...

Multi-scale fusion semantic enhancement network for medical image segmentation.

Scientific reports
The application of sophisticated computer vision techniques for medical image segmentation (MIS) plays a vital role in clinical diagnosis and treatment. Although Transformer-based models are effective at capturing global context, they are often ineff...

Cervical cancer prediction using machine learning models based on routine blood analysis.

Scientific reports
Cervical cancer (CC) is the fourth most common cancer among women globally. The key to preventing and treating CC is early detection, diagnosis, and treatment. This study aimed to develop an interpretable model for predicting CC risk using routine bl...

The construction of HMME-PDT efficacy prediction model for port-wine stain based on machine learning algorithms.

Scientific reports
Hematoporphyrin monomethyl ether-photodynamic therapy (HMME-PDT) is a safe and effective treatment for port-wine stain (PWS). Comprehensive methods for predicting HMME-PDT efficacy based on clinical factors are lacking. This study aims to develop and...

End-to-end feature fusion for jointly optimized speech enhancement and automatic speech recognition.

Scientific reports
Speech enhancement (SE) and automatic speech recognition (ASR) in real-time processing involve improving the quality and intelligibility of speech signals on the fly, ensuring accurate transcription as the speech unfolds. SE eliminates unwanted backg...

A deep dive into artificial intelligence with enhanced optimization-based security breach detection in internet of health things enabled smart city environment.

Scientific reports
Internet of Health Things (IoHT) plays a vital role in everyday routine by giving electronic healthcare services and the ability to improve patient care quality. IoHT applications and devices become widely susceptible to cyber-attacks as the tools ar...

A multi-modal graph-based framework for Alzheimer's disease detection.

Scientific reports
We propose a compositional graph-based Machine Learning (ML) framework for Alzheimer's disease (AD) detection that constructs complex ML predictors from modular components. In our directed computational graph, datasets are represented as nodes [Formu...

A dual encoder network with multiscale feature fusion and multiple pooling channel spatial attention for skin scar image segmentation.

Scientific reports
Skin scar is a prevalent dermatological concern that impacts both aesthetic appearance and psychological well-being, making precise delineation of scar tissue essential for clinical treatment. To address the challenge of scar image segmentation, this...

Enhanced security for medical images using a new 5D hyper chaotic map and deep learning based segmentation.

Scientific reports
Medical image encryption is important for maintaining the confidentiality of sensitive medical data and protecting patient privacy. Contemporary healthcare systems store significant patient data in text and graphic form. This research proposes a New ...

GAINSeq: glaucoma pre-symptomatic detection using machine learning models driven by next-generation sequencing data.

Scientific reports
Congenital glaucoma, a complex and diverse condition, presents considerable difficulties in its identification and categorization. This research used Next Generation Sequencing (NGS) whole-exome data to create a categorization framework using machine...