AIMC Topic: Humans

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Deep caries detection using deep learning: from dataset acquisition to detection.

Clinical oral investigations
OBJECTIVES: The study aims to address the global burden of dental caries, a highly prevalent disease affecting billions of individuals, including both children and adults. Recognizing the significant health challenges posed by untreated dental caries...

Advances in Artificial Intelligence for automated knee osteoarthritis classification using the IKDC system.

European journal of orthopaedic surgery & traumatology : orthopedie traumatologie
INTRODUCTION: Knee osteoarthritis is one of the most prevalent and debilitating musculoskeletal diseases, with a high incidence among the elderly population. Early detection and accurate classification can improve clinical outcomes for affected patie...

MoCHI: neural networks to fit interpretable models and quantify energies, energetic couplings, epistasis, and allostery from deep mutational scanning data.

Genome biology
We present MoCHI, a tool to fit interpretable models using deep mutational scanning data. MoCHI infers free energy changes, as well as interaction terms (energetic couplings) for specified biophysical models, including from multimodal phenotypic data...

How to identify patient perception of AI voice robots in the follow-up scenario? A multimodal identity perception method based on deep learning.

Journal of biomedical informatics
OBJECTIVES: Post-discharge follow-up stands as a critical component of post-diagnosis management, and the constraints of healthcare resources impede comprehensive manual follow-up. However, patients are less cooperative with AI follow-up calls or may...

The Role of Artificial Intelligence and Machine Learning in Accelerating the Discovery and Development of Nanomedicine.

Pharmaceutical research
The unique potential of nanomedicine to address challenging health issues is rapidly advancing the field, leading to the generation of more effective products. However, these complex systems often pose several challenges with respect to their design ...

Application of Artificial Intelligence in Symptom Monitoring in Adult Cancer Survivorship: A Systematic Review.

JCO clinical cancer informatics
PURPOSE: The adoption of artificial intelligence (AI) in health care may afford new avenues for personalized and patient-centered care. This systematic review explored the role of AI in symptom monitoring for adult cancer survivors.

How to incorporate generative artificial intelligence in nephrology fellowship education.

Journal of nephrology
Traditional nephrology education faces challenges due to expanding medical knowledge, case complexity, and personalized learning needs. Generative artificial intelligence (AI), like ChatGPT, offers potential solutions to enhance nephrology education ...

Carotid Vessel Wall Segmentation Through Domain Aligner, Topological Learning, and Segment Anything Model for Sparse Annotation in MR Images.

IEEE transactions on medical imaging
Medical image analysis poses significant challenges due to limited availability of clinical data, which is crucial for training accurate models. This limitation is further compounded by the specialized and labor-intensive nature of the data annotatio...

Mitigating Aberration-Induced Noise: A Deep Learning-Based Aberration-to- Aberration Approach.

IEEE transactions on medical imaging
One of the primary sources of suboptimal image quality in ultrasound imaging is phase aberration. It is caused by spatial changes in sound speed over a heterogeneous medium, which disturbs the transmitted waves and prevents coherent summation of echo...

Multi-Label Chest X-Ray Image Classification With Single Positive Labels.

IEEE transactions on medical imaging
Deep learning approaches for multi-label Chest X-ray (CXR) images classification usually require large-scale datasets. However, acquiring such datasets with full annotations is costly, time-consuming, and prone to noisy labels. Therefore, we introduc...