AIMC Topic: Algorithms

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Fuzzy quantum machine learning (FQML) logic for optimized disease prediction.

Computers in biology and medicine
Quantum computing, based on quantum mechanics, has evolved due to the cross-pollination of concepts, methods, and strategies. The fusion of quantum computing with machine learning (ML) algorithms has shown satisfactory results in the case of low dime...

Review learning: Real world validation of privacy preserving continual learning across medical institutions.

Computers in biology and medicine
When a deep learning model is trained sequentially on different datasets, it often forgets the knowledge learned from previous data, a problem known as catastrophic forgetting. This damages the model's performance on diverse datasets, which is critic...

Efficient estimation of plant species diversity in desert regions using UAV-based quadrats and advanced machine learning techniques.

Journal of environmental management
Understanding the distribution of plant species diversity(PSD) along spatial and environmental gradients is essential for implementing effective conservation strategies. However, effective monitoring of large-scale PSD in desert regions remain challe...

Enhanced slime mould algorithm with chaotic and orthogonal optimization-based learning for improved severity prediction accuracy in malaria patient outcomes.

Computers in biology and medicine
Malaria remains a critical health challenge in developing countries, particularly in Africa, where it disproportionately affects vulnerable populations. Accurate malaria severity prediction is important for proper treatment and improved patient survi...

A Master-Follower Teleoperation System for Robotic Catheterisation: Design, Characterisation and Tracking Control.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Over the past 2 decades, telerobotic systems with robot-mediated, minimally invasive techniques, have mitigated radiation exposure for medical staff and extended medical services to remote areas. To enhance these services, master-follower...

An Optimized Framework of QSM Mask Generation Using Deep Learning: QSMmask-Net.

NMR in biomedicine
Quantitative susceptibility mapping (QSM) provides the spatial distribution of magnetic susceptibility within tissues through sequential steps: phase unwrapping and echo combination, mask generation, background field removal, and dipole inversion. Ac...

AI-powered precision medicine: utilizing genetic risk factor optimization to revolutionize healthcare.

NAR genomics and bioinformatics
The convergence of artificial intelligence (AI) and biomedical data is transforming precision medicine by enabling the use of genetic risk factors (GRFs) for customized healthcare services based on individual needs. Although GRFs play an essential ro...

Oral cavity carcinoma detection using BAT algorithm-optimized machine learning models with transfer learning and random sampling.

Computers in biology and medicine
BACKGROUND: Oral cavity carcinoma remains a major public health concern, where early and accurate detection is vital for improving patient outcomes and survival rates. Current diagnostic systems often face challenges such as limited feature selection...

Deep learning-driven imaging of cell division and cell growth across an entire eukaryotic life cycle.

Molecular biology of the cell
The life cycle of eukaryotic microorganisms involves complex transitions between states such as dormancy, mating, meiosis, and cell division, which are often studied independently from each other. Therefore, most microbial life cycles are theoretical...

A transformer-based framework for temporal health event prediction with graph-enhanced representations.

Journal of biomedical informatics
OBJECTIVE: Deep learning approaches have demonstrated significant potential in predicting temporal health events in recent years. However, existing methods have not fully leveraged the complex interactions among comorbidities and have overlooked imba...