Artificial Intelligence Medical Compendium

This study introduces a novel approach for quantitatively evaluating debonding in exterior ceramic tile panels using Lamb wave signals and a data-driven deep learning methodology. Leveraging a two-dimensional convolutional neural network (2D-CNN), ti... read more 

Parameter-efficient fine-tuning (PEFT) has emerged as a critical paradigm for adapting large pre-trained models to downstream tasks, offering a balance between computational efficiency and model performance. Among these methods, Low-Rank Adaptation (... read more 

A kind of recurrent neural network (RNN) specialized in solving time-varying problems has wide applications in various fields, where the RNN with integral terms (RNN-IT) as a state-of-art method plays an important role in rejecting noise. However, th... read more 

Natural language processing systems (NLPs) and large language models (LLMs) have the potential to revolutionize hand surgery by streamlining workflows, enhancing patient-care, and advancing research capabilities. NLPs are particularly adept at proces... read more 

Artificial intelligence is transforming medical research and health care, with transformers playing a crucial role in advancing medical data analysis. Originally developed for natural language processing, transformers have successfully applied their ... read more 

Artificial intelligence-enabled remote patient monitoring is transforming hand surgery by using advanced technologies like machine learning and computer vision to track patient recovery in real-time. Wearable devices and sensors collect objective dat... read more 

Since the conception of the artificial neuron in 1943, neural networks have developed into multi-layer models enabling image recognition, speech recognition, personalized recommendation for web browsing, social media content, and virtual assistants. ... read more 

Artificial intelligence (AI) has rapidly advanced in healthcare, demonstrating significant potential in analyzing large, heterogeneous datasets using optimized algorithms for disease prediction and personalized treatment. Assisted reproductive techno... read more 

OBJECTIVE: To assess the ability of large language models (LLMs) to accurately simplify lumbar spine magnetic resonance imaging (MRI) reports. MATERIALS AND METHODS: Patients who underwent lumbar decompression and/or fusion surgery in 2022 at one ter... read more 

CONTEXT: Early detection of acute leukemia (AL) is crucial for timely intervention and improved outcomes. Machine learning (ML) models provide a promising approach for early screening and rapid diagnosis of AL, minimizing delays in referral. OBJECTIV... read more