AIMC Topic: Algorithms

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Deep learning-based CAD system for Alzheimer's diagnosis using deep downsized KPLS.

Scientific reports
Alzheimer's disease (AD) is the most prevalent type of dementia. It is linked with a gradual decline in various brain functions, such as memory. Many research efforts are now directed toward non-invasive procedures for early diagnosis because early d...

Machine-learning-guided identification of protein secondary structures using spectral and structural descriptors.

Biomaterials science
Interrogation of the secondary structures of proteins is essential for designing and engineering more effective and safer protein-based biomaterials and other classes of theranostic materials. Protein secondary structures are commonly assessed using ...

Dose calculation in nuclear medicine with magnetic resonance imaging images using Monte Carlo method.

Radiation protection dosimetry
In recent years, scientists have been trying to convert magnetic resonance imaging (MRI) images into computed tomography (CT) images for dose calculations while taking advantage of the benefits of MRI images. The main approaches for image conversion ...

Enhancing patient rehabilitation outcomes: artificial intelligence-driven predictive modeling for home discharge in neurological and orthopedic conditions.

Journal of neuroengineering and rehabilitation
In recent years, the fusion of the medical and computer science domains has gained significant traction in the scientific research landscape. Progress in both fields has enabled the generation of a vast amount of data used for making predictions and ...

Prediction of one-year recurrence among breast cancer patients undergone surgery using artificial intelligence-based algorithms: a retrospective study on prognostic factors.

BMC cancer
BACKGROUND AND AIM: Breast cancer is highly prevalent, with an increasing trend in women globally. Although the survival of breast cancer is relatively high, the recurrence rate is also high, demanding effective predictive solutions to breast cancer ...

Development of time to event prediction models using federated learning.

BMC medical research methodology
BACKGROUND: In a wide range of diseases, it is necessary to utilize multiple data sources to obtain enough data for model training. However, performing centralized pooling of multiple data sources, while protecting each patients' sensitive data, can ...

Interpretable machine learning for predicting optimal surgical timing in polytrauma patients with TBI and fractures to reduce postoperative infection risk.

Scientific reports
This retrospective study leverages machine learning to determine the optimal timing for fracture reconstruction surgery in polytrauma patients, focusing on those with concomitant traumatic brain injury. The analysis included 218 patients admitted to ...

Digital image enhancement using deep learning algorithm in 3D heads-up vitreoretinal surgery.

Scientific reports
This study aims to predict the optimal imaging parameters using a deep learning algorithm in 3D heads-up vitreoretinal surgery and assess its effectiveness on improving the vitreoretinal surface visibility during surgery. To develop the deep learning...

Computational hybrid analysis of drug diffusion in three-dimensional domain with the aid of mass transfer and machine learning techniques.

Scientific reports
Molecular diffusion of drugs is of major importance for development and understanding drug delivery systems. Indeed, the main phenomenon which is controlling the rate of release is molecular diffusion which can be controlled via different phenomena s...