AIMC Topic: Deep Learning

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Multi-stain deep learning prediction model of treatment response in lupus nephritis based on renal histopathology.

Kidney international
The response of the kidney after induction treatment is one of the determinants of prognosis in lupus nephritis, but effective predictive tools are lacking. Here, we sought to apply deep learning approaches on kidney biopsies for treatment response p...

Evaluation of the effectiveness of panoramic radiography in impacted mandibular third molars on deep learning models developed with findings obtained with cone beam computed tomography.

Oral radiology
OBJECTIVE: The aim of this study is to determine the contact relationship and position of impacted mandibular third molar teeth (IMM) with the mandibular canal (MC) in panoramic radiography (PR) images using deep learning (DL) models trained with the...

Artificial intelligence in in-vitro fertilization (IVF): A new era of precision and personalization in fertility treatments.

Journal of gynecology obstetrics and human reproduction
In-vitro fertilization (IVF) has been a transformative advancement in assisted reproductive technology. However, success rates remain suboptimal, with only about one-third of cycles resulting in pregnancy and fewer leading to live births. This narrat...

MrSeNet: Electrocardiogram signal denoising based on multi-resolution residual attention network.

Journal of electrocardiology
Electrocardiography (ECG) is a widely used, non-invasive, and cost-effective diagnostic method that plays a crucial role in the early detection and management of cardiac conditions. However, the ECG signal is easily disrupted by various noise signals...

Deep Learning Unravels Differences Between Kinematic and Kinetic Gait Cycle Time Series from Two Control Samples of Healthy Children Assessed in Two Different Gait Laboratories.

Sensors (Basel, Switzerland)
We investigate the application of deep learning in comparing gait cycle time series from two groups of healthy children, each assessed in different gait laboratories. Both laboratories used similar gait analysis protocols with minimal differences in ...

Porter 6: Protein Secondary Structure Prediction by Leveraging Pre-Trained Language Models (PLMs).

International journal of molecular sciences
Accurately predicting protein secondary structure (PSSP) is crucial for understanding protein function, which is foundational to advancements in drug development, disease treatment, and biotechnology. Researchers gain critical insights into protein f...

Survival prediction of glioblastoma patients using machine learning and deep learning: a systematic review.

BMC cancer
Glioblastoma Multiforme (GBM), classified as a grade IV glioma by the World Health Organization (WHO), is a prevalent and notably aggressive form of brain tumor derived from glial cells. It stands as one of the most severe forms of primary brain canc...

Applications and Future Prospects of Medical LLMs: A Survey Based on the M-KAT Conceptual Framework.

Journal of medical systems
The success of large language models (LLMs) in general areas have sparked a wave of research into their applications in the medical field. However, enhancing the medical professionalism of these models remains a major challenge. This study proposed a...

Descriptive overview of AI applications in x-ray imaging and radiotherapy.

Journal of radiological protection : official journal of the Society for Radiological Protection
Artificial intelligence (AI) is transforming medical radiation applications by handling complex data, learning patterns, and making accurate predictions, leading to improved patient outcomes. This article examines the use of AI in optimising radiatio...

Preictal period optimization for deep learning-based epileptic seizure prediction.

Journal of neural engineering
. Accurate seizure prediction could prove critical for improving patient safety and quality of life in drug-resistant epilepsy. While deep learning-based approaches have shown promising performance using scalp electroencephalogram (EEG) signals, the ...