AIMC Topic: Artificial Intelligence

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Post-Mortem imaging biobanks: Building data for reproducibility, standardization, and AI integration.

European journal of radiology
In recent years, post-mortem imaging has advanced with techniques such as Post-Mortem Computed Tomography (PMCT) and Post-Mortem Magnetic Resonance imaging (PMMR). PMCT is particularly useful for assessing skeletal injuries, vascular lesions, and est...

The need for balancing 'black box' systems and explainable artificial intelligence: A necessary implementation in radiology.

European journal of radiology
Radiology is one of the medical specialties most significantly impacted by Artificial Intelligence (AI). AI systems, particularly those employing machine and deep learning, excel in processing large datasets and comparing images from similar contexts...

Is it necessary? A framework for assessing the utility of A.I. in HRM practices.

Acta psychologica
Artificial Intelligence is expected to be a value-adding intervention in HRM processes; however, there is still a large gap between its perception of value-addition and its actual utility. In this article, we utilize transaction cost and resource-bas...

Advanced 3D Food Printing with Simultaneous Cooking and Generative AI Design.

Advanced materials (Deerfield Beach, Fla.)
3D food printing is an indispensable technology for emerging food technologies. However, conventional nonconcurrent postprocessing methods limit the final food quality, including the unappealing nature of food ink modification, imperfections in retai...

Artificial intelligence in medical imaging: From task-specific models to large-scale foundation models.

Chinese medical journal
Artificial intelligence (AI), particularly deep learning, has demonstrated remarkable performance in medical imaging across a variety of modalities, including X-ray, computed tomography (CT), magnetic resonance imaging (MRI), ultrasound, positron emi...

Integrating artificial intelligence into medical curricula: perspectives of faculty and students in South Korea.

Korean journal of medical education
PURPOSE: With the accelerated adoption of artificial intelligence (AI) in medicine, the integration of AI education into medical school curricula is gaining significant attention. This study aimed to gather the perceptions of faculty members and stud...

The radiologist as an independent "third party" to the patient and clinicians in the era of generative AI.

La Radiologia medica
Radiologists are crucial in the diagnostic workflow. They must maintain an independent perspective, being a "third party" to the patients and referral clinicians. This is important when documenting the absence of relevant abnormalities or providing i...

Deep Learning for Lumbar Disc Herniation Diagnosis and Treatment Decision-Making Using Magnetic Resonance Imagings: A Retrospective Study.

World neurosurgery
BACKGROUND: Lumbar disc herniation (LDH) is a common cause of back and leg pain. Diagnosis relies on clinical history, physical exam, and imaging, with magnetic resonance imaging (MRI) being an important reference standard. While artificial intellige...

Untargeted Lipidomic Biomarkers for Liver Cancer Diagnosis: A Tree-Based Machine Learning Model Enhanced by Explainable Artificial Intelligence.

Medicina (Kaunas, Lithuania)
: Liver cancer ranks among the leading causes of cancer-related mortality, necessitating the development of novel diagnostic methods. Deregulated lipid metabolism, a hallmark of hepatocarcinogenesis, offers compelling prospects for biomarker identifi...

Artificial Intelligence and Predictive Modeling in the Management and Treatment of Episodic Migraine.

Current pain and headache reports
PURPOSE OF REVIEW: Artificial intelligence (AI) has impacted different aspects of headache medicine, from history taking and diagnosis to drug development. AI has been shown to have predictive modeling in helping diagnose migraine and assist with pat...