AIMC Topic: Algorithms

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Latent space autoencoder generative adversarial model for retinal image synthesis and vessel segmentation.

BMC medical imaging
Diabetes is a widespread condition that can lead to serious vision problems over time. Timely identification and treatment of diabetic retinopathy (DR) depend on accurately segmenting retinal vessels, which can be achieved through the invasive techni...

M-DeepAssembly: enhanced DeepAssembly based on multi-objective multi-domain protein conformation sampling.

BMC bioinformatics
BACKGROUND: Association and cooperation among structural domains play an important role in protein function and drug design. Despite remarkable advancements in highly accurate single-domain protein structure prediction through the collaborative effor...

Optimizing non small cell lung cancer detection with convolutional neural networks and differential augmentation.

Scientific reports
Lung cancer remains one of the leading causes of cancer-related deaths worldwide, with early detection being critical to improving patient outcomes. Recent advancements in deep learning have shown promise in enhancing diagnostic accuracy, particularl...

Integrating SAM priors with U-Net for enhanced multiclass cell detection in digital pathology.

Scientific reports
In digital pathology, the accurate detection, segmentation, and classification of cells are pivotal for precise pathological diagnosis. Traditionally, pathologists manually segment cells from pathological images to facilitate diagnosis based on these...

Advanced holographic convolutional dense networks and Tangent runner optimization for enhanced polycystic ovarian disease classification.

Scientific reports
Polycystic Ovarian Disease (PCOD) is among the most prevalent endocrine disorders complicating the health of innumerable women worldwide due to lack of diagnosis and appropriate management. The diagnosis of PCOD, along with proper classification with...

An efficient patient's response predicting system using multi-scale dilated ensemble network framework with optimization strategy.

Scientific reports
The forecasting of a patient's response to radiotherapy and the likelihood of experiencing harmful long-term health impacts would considerably enhance individual treatment plans. Due to the continuous exposure to radiation, cardiovascular disease and...

An attention based hybrid approach using CNN and BiLSTM for improved skin lesion classification.

Scientific reports
Skin lesions remain a significant global health issue, with their incidence rising steadily over the past few years. Early and accurate detection is crucial for effective treatment and improving patient outcomes. This work explores the integration of...

GelGenie: an AI-powered framework for gel electrophoresis image analysis.

Nature communications
Gel electrophoresis is a ubiquitous laboratory method for the separation and semi-quantitative analysis of biomolecules. However, gel image analysis principles have barely advanced for decades, in stark contrast to other fields where AI has revolutio...

Enhancing Cardiopulmonary Resuscitation Quality Using a Smartwatch: Neural Network Approach for Algorithm Development and Validation.

JMIR mHealth and uHealth
BACKGROUND: Sudden cardiac arrest is a major cause of mortality, necessitating immediate and high-quality cardiopulmonary resuscitation (CPR) for improved survival rates. High-quality CPR is defined by chest compressions at a rate of 100-120 per minu...

Replacing non-biomedical concepts improves embedding of biomedical concepts.

PloS one
Embeddings are semantically meaningful representations of words in a vector space, commonly used to enhance downstream machine learning applications. Traditional biomedical embedding techniques often replace all synonymous words representing biologic...