AIMC Topic: Humans

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DTreePred: an online viewer based on machine learning for pathogenicity prediction of genomic variants.

BMC bioinformatics
BACKGROUND: A significant challenge in precision medicine is confidently identifying mutations detected in sequencing processes that play roles in disease treatment or diagnosis. Furthermore, the lack of representativeness of single nucleotide varian...

The Role of ChatGPT in osteoporosis management: a comparative analysis with clinical expertise.

Archives of osteoporosis
UNLABELLED: This study evaluates the role of ChatGPT in osteoporosis management, demonstrating 91% diagnostic accuracy and significantly faster response times compared to clinicians. The findings highlight the potential for artificial intelligence (A...

The use of artificial intelligence-based Siamese neural network in personalized guidance for sports dance teaching.

Scientific reports
This work aims to explore an accurate and effective method for recognizing dance movement features, providing precise personalized guidance for sports dance teaching. First, a human skeletal graph is constructed. A graph convolutional network (GCN) i...

Novel deep learning algorithm based MRI radiomics for predicting lymph node metastases in rectal cancer.

Scientific reports
To explore the value of applying the MRI-based radiomic nomogram for predicting lymph node metastasis (LNM) in rectal cancer (RC). This retrospective analysis used data from 430 patients with RC from two medical centers. The patients were categorized...

Voice biomarkers as prognostic indicators for Parkinson's disease using machine learning techniques.

Scientific reports
Many people suffer from Parkinson's disease globally, a complicated neurological condition caused by the deficiency of dopamine, an organic chemical responsible for regulating movement in individuals. Patients with Parkinson face muscle stiffness or ...

Hybrid convolutional neural network and bi-LSTM model with EfficientNet-B0 for high-accuracy breast cancer detection and classification.

Scientific reports
Breast cancer detection remains one of the most challenging problems in medical imaging. We propose a novel hybrid model that integrates Convolutional Neural Networks (CNNs), Bidirectional Long Short-Term Memory (Bi-LSTM) networks, and EfficientNet-B...

One-class support vector machines for detecting population drift in deployed machine learning medical diagnostics.

Scientific reports
Machine learning (ML) models are increasingly being applied to diagnose and predict disease, but face technical challenges such as population drift, where the training and real-world deployed data distributions differ. This phenomenon can degrade mod...

Natural language processing models reveal neural dynamics of human conversation.

Nature communications
Through conversation, humans engage in a complex process of alternating speech production and comprehension to communicate. The neural mechanisms that underlie these complementary processes through which information is precisely conveyed by language,...

Extracting Pulmonary Embolism Diagnoses From Radiology Impressions Using GPT-4o: Large Language Model Evaluation Study.

JMIR medical informatics
BACKGROUND: Pulmonary embolism (PE) is a critical condition requiring rapid diagnosis to reduce mortality. Extracting PE diagnoses from radiology reports manually is time-consuming, highlighting the need for automated solutions. Advances in natural l...

Young Adult Perspectives on Artificial Intelligence-Based Medication Counseling in China: Discrete Choice Experiment.

Journal of medical Internet research
BACKGROUND: As artificial intelligence (AI) permeates the current society, the young generation is becoming increasingly accustomed to using digital solutions. AI-based medication counseling services may help people take medications more accurately a...