AIMC Topic: Artificial Intelligence

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Artificial intelligence meets brain theory (again).

Biological cybernetics
After noting the cybernetic origins of Kybernetik/ Biological Cybernetics, we respond to the Editorial by Fellous et al. (2025) and then analyze talks from the NIH BRAIN NeuroAI 2024 Workshop to get one "snapshot" of the state of the conversation bet...

Artificial intelligence - based approaches based on random forest algorithm for signal analysis: Potential applications in detection of chemico - biological interactions.

Chemico-biological interactions
Random Forest (RF) is a powerful ensemble-based supervised machine learning technique that builds multiple decision trees using bootstrap aggregating and random feature selection to improve classification and regression accuracy while reducing overfi...

The diagnostic model from semi-supervised cross modality transformation improved the distinguished ability of X-rays for pulmonary tuberculosis.

Clinical radiology
BACKGROUND: Early diagnosis of tuberculosis is particularly difficult in resource-poor areas. Traditional chest X-rays (CXR) have limited accuracy, while CT scans are costly and involve radiation exposure. The study aims to improve the diagnostic acc...

Task-specific versus general-purpose AI models in ECG analysis: A comparative study with emergency medicine specialists.

The American journal of emergency medicine
PURPOSE: To evaluate and compare the diagnostic accuracy of three Artificial intelligence (AI) models-GPT-4o, Canva-GPT, and ECG Reader-GPT-against emergency medicine specialists (EMSs) in electrocardiogram (ECG) interpretation using a standardized a...

Pulmonary hypertension: diagnostic aspects-what is the role of imaging?

Current opinion in cardiology
PURPOSE OF REVIEW: The role of imaging in diagnosis of pulmonary hypertension is multifaceted, spanning from estimation of pulmonary arterial pressures, understanding pulmonary artery-right ventricular interaction, and identification of the cause. Th...

Advancements in strabismus diagnosis: A comprehensive systematic review of artificial intelligence and digital health applications.

Experimental eye research
PURPOSE: To review the accuracy of artificial intelligence (AI) and digital health applications in the screening and diagnosis of strabismus.

Fatigue monitoring using wearables and AI: Trends, challenges, and future opportunities.

Computers in biology and medicine
Monitoring fatigue is essential for improving safety, particularly for people who work long shifts or in high-demand and high-risk environments such as transportation, construction, healthcare, and manufacturing. The development of wearable technolog...

Artificial Intelligence-Based Detection of Central Retinal Artery Occlusion Within 4.5 Hours on Standard Fundus Photographs.

Journal of the American Heart Association
BACKGROUND: Prompt diagnosis of acute central retinal artery occlusion (CRAO) is crucial for therapeutic management and stroke prevention. However, most stroke centers lack onsite ophthalmic expertise before considering fibrinolytic treatment. This s...

The singing style of female roles in ethnic opera under artificial intelligence and deep neural networks.

Scientific reports
With the rapid advancement of artificial intelligence technology, efficiently extracting and analyzing music performance style features has become an important topic in the field of music information processing. This work focuses on the classificatio...

AI-supported versus manual microscopy of Kato-Katz smears for diagnosis of soil-transmitted helminth infections in a primary healthcare setting.

Scientific reports
Soil-transmitted helminths primarily comprise Ascaris lumbricoides, Trichuris trichiura, and hookworms, infecting more than 600 million people globally, particularly in underserved communities. Manual microscopy of Kato-Katz thick smears is a widely ...