AIMC Topic: Neural Networks, Computer

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Fast and accurate lung cancer subtype classication and localization based on Intraoperative frozen sections of lung adenocarcinoma.

Biomedical physics & engineering express
Current lung cancer diagnostic techniques primarily focus on tissue subtype classification, yet remain inadequate in distinguishing pathological progression subtypes (particularly between adenocarcinomaand invasive adenocarcinoma) on frozen sections....

Foster noisy label learning by exploiting noise-induced distortion in foreground localization.

Neural networks : the official journal of the International Neural Network Society
Large-scale, well-annotated datasets are crucial for training deep neural networks. However, the prevalence of noisy-labeled samples can cause irreversible impairment to the generalization of models. Existing approaches have attempted to mitigate the...

Application Value of Deep Learning-Based AI Model in the Classification of Breast Nodules.

British journal of hospital medicine (London, England : 2005)
Breast nodules are highly prevalent among women, and ultrasound is a widely used screening tool. However, single ultrasound examinations often result in high false-positive rates, leading to unnecessary biopsies. Artificial intelligence (AI) has dem...

sEntIMeldCL: Enhancing explicit knowledge via Uniform-based Implicit Contrastive Mechanism for Aspect-Level Sentiment Analysis.

Neural networks : the official journal of the International Neural Network Society
Aspect-level sentiment analysis (ALSA) is a fine-grained task which consists of aspect terms and sentiment polarities within sentences. Numerous research studies only focus on the syntactical dependencies between words, ignoring the impact of negatio...

Automated analysis of mouse rearing using deep learning.

Journal of pharmacological sciences
Rodent rearing behavior is frequently assessed as an indicator of anxiety and exploratory tendencies. This study developed a convolutional recurrent neural network (CRNN) model to detect mouse rearing using overhead videos. Behavioral data from C57BL...

Predicting drug-drug interactions: A deep learning approach with GCN-based collaborative filtering.

Artificial intelligence in medicine
The use of combination drugs among patients is increasing due to effectiveness compared to monotherapies. However, healthcare providers should continue to be concerned about the potential risks associated with patient safety arising from drug-drug in...

Redefining parameter-efficiency in ADHD diagnosis: A lightweight attention-driven kolmogorov-arnold network with reduced parameter complexity and a novel activation function.

Psychiatry research. Neuroimaging
As deep learning continues to advance in medical analysis, the increasing complexity of models, particularly Convolutional Neural Networks (CNNs), presents significant challenges related to interpretability, computational costs, and real-world applic...

KEM-IoMT: Knowledge graph embedding-enhanced accurate medical service recommendation against diabetes.

Computers in biology and medicine
The Internet of Medical Things (IoMT)-enhanced Recommender System (RS) acquired swift advancement in configuring diverse medical data into intelligent systems to generate personalized medical services. However, due to the heterogeneous and complex na...

A method for feature division of Soccer Foul actions based on salience image semantics.

PloS one
The purpose of this study is to realize the automatic identification and classification of fouls in football matches and improve the overall identification accuracy. Therefore, a Deep Learning-Based Saliency Prediction Model (DLSPM) is proposed. DLSP...

Adaptive weighted dual MAML: Proposing a novel method for the automated diagnosis of partial sleep deprivation.

PloS one
INTRODUCTION: Sleep disorders significantly disrupt normal sleep patterns and pose serious health risks. Traditional diagnostic methods, such as questionnaires and polysomnography, often require extensive time and are susceptible to errors. This high...