AIMC Topic: Artificial Intelligence

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Being diagnosed with a rhabdomyosarcoma in the era of artificial intelligence: Whom can we trust?

Pediatric blood & cancer
In the era of big data, young patients may be overwhelmed by artificial intelligence-based tools, like chatbots. Five clinical experts were asked to evaluate the performance of the most currently used chatbots in providing information on a rare cance...

Zero-Biased Bionic Fingertip E-Skin with Multimodal Tactile Perception and Artificial Intelligence for Augmented Touch Awareness.

Advanced materials (Deerfield Beach, Fla.)
Electronic skins (E-Skins) are crucial for future robotics and wearable devices to interact with and perceive the real world. Prior research faces challenges in achieving comprehensive tactile perception and versatile functionality while keeping syst...

Novel use of deep neural networks on photographic identification of epaulette sharks (Hemiscyllium ocellatum) across life stages.

Journal of fish biology
Photographic identification (photo ID) is an established method that is used to count animals and track individuals' movements. This method performs well with some species of elasmobranchs (i.e., sharks, skates, and rays) where individuals have disti...

Assessing the performance of AI-assisted technicians in liver segmentation, Couinaud division, and lesion detection: a pilot study.

Abdominal radiology (New York)
BACKGROUND: In patients with primary and secondary liver cancer, the number and sizes of lesions, their locations within the Couinaud segments, and the volume and health status of the future liver remnant are key for informing treatment planning. Cur...

Randomized algorithms for large-scale dictionary learning.

Neural networks : the official journal of the International Neural Network Society
Dictionary learning is an important sparse representation algorithm which has been widely used in machine learning and artificial intelligence. However, for massive data in the big data era, classical dictionary learning algorithms are computationall...

Use of artificial intelligence-guided echocardiography to detect cardiac dysfunction and heart valve disease in rural and remote areas: Rationale and design of the AGILE-echo trial.

American heart journal
BACKGROUND: Transthoracic echocardiography (TTE) is essential in the diagnosis of cardiovascular diseases (CVD), including but not limited to heart failure (HF) and heart valve disease (HVD). However, its dependence on expert acquisition means that i...

Artificial intelligence-based classification of cardiac autonomic neuropathy from retinal fundus images in patients with diabetes: The Silesia Diabetes Heart Study.

Cardiovascular diabetology
BACKGROUND: Cardiac autonomic neuropathy (CAN) in diabetes mellitus (DM) is independently associated with cardiovascular (CV) events and CV death. Diagnosis of this complication of DM is time-consuming and not routinely performed in the clinical prac...

Attitude of aspiring orthopaedic surgeons towards artificial intelligence: a multinational cross-sectional survey study.

Archives of orthopaedic and trauma surgery
INTRODUCTION: The purpose of this study was to evaluate the perspectives of aspiring orthopaedic surgeons on artificial intelligence (AI), analysing how gender, AI knowledge, and technical inclination influence views on AI. Additionally, the extent t...

A review of ophthalmology education in the era of generative artificial intelligence.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
PURPOSE: To explore the integration of generative AI, specifically large language models (LLMs), in ophthalmology education and practice, addressing their applications, benefits, challenges, and future directions.