AIMC Topic: Humans

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Development of artificial intelligence-based algorithms for the process of human identification through dental evidence.

International journal of legal medicine
INTRODUCTION: Forensic Odontology plays a crucial role in medicolegal identification by comparing dental evidence in antemortem (AM) and postmortem (PM) dental records, including orthopantomograms (OPGs). Due to the complexity and time-consuming natu...

Artificial intelligence-assisted identification and assessment of mandibular asymmetry on panoramic radiography.

American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics
INTRODUCTION: Mandibular symmetry is crucial in orthodontic diagnosis and treatment planning. This study aimed to establish an artificial intelligence (AI) method to automatically and accurately identify mandibular landmarks and assess asymmetry via ...

Machine learning-based exploration of Umami peptides in Pixian douban: Insights from virtual screening, molecular docking, and post-translational modifications.

Food chemistry
Pixian Doubanjiang (PXDB)'s distinctive umami profile is primarily attributed to its unique peptides; however, their structural characteristics, sensory mechanisms, and biosynthetic pathways during aging remain poorly understood. This study employed ...

Alzheimer's disease prediction using 3D-CNNs: Intelligent processing of neuroimaging data.

SLAS technology
Alzheimer's disease (AD) is a severe neurological illness that demolishes memory and brain functioning. This disease affects an individual's capacity to work, think, and behave. The proportion of individuals suffering from AD is rapidly increasing. I...

NLP-driven integration of electrophysiology and traditional Chinese medicine for enhanced diagnostics and management of postpartum pain.

SLAS technology
Postpartum pain encompasses a range of physical and emotional discomforts, often influenced by hormonal changes, physical recovery, and individual psychological states. The complex interactions between the variables can make it difficult for traditio...

Advanced NLP-driven predictive modeling for tailored treatment strategies in gastrointestinal cancer.

SLAS technology
Gastrointestinal cancer represents a significant health burden, necessitating innovative approaches for personalized treatment. This study aims to develop an advanced natural language processing (NLP)-driven predictive modeling framework for tailored...

Image classification-driven speech disorder detection using deep learning technique.

SLAS technology
Speech disorders affect an individual's ability to generate sounds or utilize the voice appropriately. Neurological, developmental, physical, and trauma may cause speech disorders. Speech impairments influence communication, social interaction, educa...

Development of a natural language processing algorithm to extract social determinants of health from clinician notes.

American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons
Disparities in access to the organ transplant waitlist are well-documented, but research into modifiable factors has been limited due to a lack of access to organized prewaitlisting data. This study aimed to develop a natural language processing (NLP...

Deep reinforcement learning for multi-targets propofol dosing.

Journal of clinical monitoring and computing
The administration of propofol for sedation or general anesthesia presents challenges due to the complex relationship between patient factors and real-time physiological responses. This study explores the application of deep reinforcement learning (D...