AIMC Topic: Deep Learning

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Dual prompt personalized federated learning in foundation models.

Scientific reports
Personalized federated learning (PFL) has garnered significant attention for its ability to address heterogeneous client data distributions while preserving data privacy. However, when local client data is limited, deep learning models often suffer f...

Development of a novel deep learning method that transforms tabular input variables into images for the prediction of SLD.

Scientific reports
Steatotic liver disease (SLD), formerly named fatty liver disease, has a prevalence estimated at 30-38% in adults. Detection of SLD is important, since prompt initiation of treatment can stop disease progression, lead to a reduction in adverse outcom...

Impact of large language models and vision deep learning models in predicting neoadjuvant rectal score for rectal cancer treated with neoadjuvant chemoradiation.

BMC medical imaging
This study aims to explore Deep Learning methods, namely Large Language Models (LLMs) and Computer Vision models to accurately predict neoadjuvant rectal (NAR) score for locally advanced rectal cancer (LARC) treated with neoadjuvant chemoradiation (N...

A dataset for recognition of Arabic accents from spoken L2 English speech (ArL2Eng).

Scientific data
This paper introduces the ArL2Eng dataset, a speech corpus of L2 English produced by native speakers of Arabic, and highlights its potential in supporting research into automated language assessment. ArL2Eng comprises audio sequences from speakers of...

Investigating the Impact of the Stationarity Hypothesis on Heart Failure Detection using Deep Convolutional Scattering Networks and Machine Learning.

Scientific reports
Detection of Cardiovascular Diseases (CVDs) has become crucial nowadays, as the World Health Organization (WHO) declares CVDs as the major leading causes of death in the globe. Moreover, the death rate due to CVDs is expected to rise in the next few ...

Advancing deep learning for expressive music composition and performance modeling.

Scientific reports
The pursuit of expressive and human-like music generation remains a significant challenge in the field of artificial intelligence (AI). While deep learning has advanced AI music composition and transcription, current models often struggle with long-t...

AI-assisted intraoperative navigation for safe right liver mobilization in pure laparoscopic donor hepatectomy: an experimental multi-institutional validation study.

Scientific reports
Minimally invasive liver surgery (MILS) offers significant benefits but faces limited adoption due to its steep learning curve. This study explores the potential of artificial intelligence (AI) in assisting the performance of major MILS by providing ...

Data Collection for Automatic Depression Identification in Spanish Speakers Using Deep Learning Algorithms: Protocol for a Case-Control Study.

JMIR research protocols
BACKGROUND: Depression is a mental health condition that affects millions of people worldwide. Although common, it remains difficult to diagnose due to its heterogeneous symptomatology. Mental health questionnaires are currently the most used assessm...

Artificial intelligence in hepatopancreatobiliary surgery for clinical outcome prediction: current perspective and future direction.

Journal of robotic surgery
The expanding and evolving role of artificial intelligence (AI) in surgery has been enhanced by the adoption of robotic-assisted surgery (RAS), which provides a platform to facilitate the integration and utilisation of AI technologies. One area where...

Deep learning-based real-time detection of head and neck tumors during radiation therapy.

Physics in medicine and biology
Clinical drivers for real-time head and neck (H&N) tumor tracking during radiation therapy (RT) are accounting for motion caused by changes to the immobilization mask fit, and to reduce mask-related patient distress by replacing the masks with patien...