AIMC Topic: Humans

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The double-edged sword of generative AI: surpassing an expert or a deceptive "false friend"?

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: Generative artificial intelligence (AI), ChatGPT being the most popular example, has been extensively assessed for its capability to respond to medical questions, such as queries in spine treatment approaches or technological adva...

Morphological alterations of the thymus gland in individuals with schizophrenia.

Molecular psychiatry
Despite its critical function in the immune system and accumulating evidence of immunological abnormalities in schizophrenia, the thymus has long been overlooked. We aimed to investigate thymic morphological alterations and their corresponding hetero...

Development of Artificial Intelligence-Supported Automatic Three-Dimensional Surface Cephalometry.

Orthodontics & craniofacial research
OBJECTIVE: Surface-based three-dimensional (3D) cephalometry provides detailed clinical information for the analysis of craniofacial structures. This study aimed to develop an automated 3D surface cephalometry system using mesh fitting based on landm...

An early prediction model for gestational diabetes mellitus created using machine learning algorithms.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
OBJECTIVE: To investigate high-risk factors for gestational diabetes mellitus (GDM) in early pregnancy through an analysis of demographic and clinical data, and to develops a machine-learning-based prediction model to enhance early diagnosis and inte...

Efficient Brain Tumor Detection and Segmentation Using DN-MRCNN With Enhanced Imaging Technique.

Microscopy research and technique
This article proposes a method called DenseNet 121-Mask R-CNN (DN-MRCNN) for the detection and segmentation of brain tumors. The main objective is to reduce the execution time and accurately locate and segment the tumor, including its subareas. The i...

Predicting the complexity of minimally invasive liver resection for hepatocellular carcinoma using machine learning.

HPB : the official journal of the International Hepato Pancreato Biliary Association
BACKGROUND: Despite technical advancements, minimally invasive liver surgery (MILS) for hepatocellular carcinoma (HCC) remains challenging. Nonetheless, effective tools to assess MILS complexity are still lacking. Machine learning (ML) models could i...

Indication model for laparoscopic repeat liver resection in the era of artificial intelligence: machine learning prediction of surgical indication.

HPB : the official journal of the International Hepato Pancreato Biliary Association
BACKGROUND: Laparoscopic repeat liver resection (LRLR) is still a challenging technique and requires a careful selection of indications. However, the current difficulty scoring system is not suitable for selecting indications. The purpose of this stu...

Natural Language Processing and soft data for motor skill assessment: A case study in surgical training simulations.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Automated surgical skill assessment using kinematic and video data (hard data) sources has been widely adopted in the literature. However, experts' opinions (soft data) in the form of free-text could be an invaluable source ...

Comparing Artificial Intelligence and Traditional Regression Models in Lung Cancer Risk Prediction Using A Systematic Review and Meta-Analysis.

Journal of the American College of Radiology : JACR
PURPOSE: Accurately identifying individuals who are at high risk of lung cancer is critical to optimize lung cancer screening with low-dose CT (LDCT). We sought to compare the performance of traditional regression models and artificial intelligence (...

Interpretable machine learning unveils key predictors and default values in an expanded database of human in vitro dermal absorption studies with pesticides.

Regulatory toxicology and pharmacology : RTP
The skin is the main route of exposure to plant protection products for operators, workers, residents, and bystanders. Assessing dermal absorption is key for evaluating pesticide exposure. The initial approach to risk assessment involves using defaul...