AIMC Topic: Algorithms

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In-Person Verification of Deep Learning Algorithm for Diabetic Retinopathy Screening Using Different Techniques Across Fundus Image Devices.

Translational vision science & technology
PURPOSE: To evaluate the clinical performance of an automated diabetic retinopathy (DR) screening model to detect referable cases at Siriraj Hospital, Bangkok, Thailand.

Neuromorphology in-sensor computing architecture based on an optical Fourier transform.

Optics letters
We propose an object recognition architecture relying on a neural network algorithm in optical sensors. Precisely, by applying the high-speed and low-power Fourier transform operation in the optical domain, we can transfer the high-cost part of the t...

Lack of Transparency and Potential Bias in Artificial Intelligence Data Sets and Algorithms: A Scoping Review.

JAMA dermatology
IMPORTANCE: Clinical artificial intelligence (AI) algorithms have the potential to improve clinical care, but fair, generalizable algorithms depend on the clinical data on which they are trained and tested.

Rise of the Machines: Artificial Intelligence and the Clinical Laboratory.

The journal of applied laboratory medicine
BACKGROUND: Artificial intelligence (AI) is rapidly being developed and implemented to augment and automate decision-making across healthcare systems. Being an essential part of these systems, laboratories will see significant growth in AI applicatio...

Artificial intelligence and machine learning in aortic disease.

Current opinion in cardiology
PURPOSE OF REVIEW: Discuss foundational concepts for artificial intelligence (AI) and review recent literature on its application to aortic disease.

Performance of a Convolutional Neural Network and Explainability Technique for 12-Lead Electrocardiogram Interpretation.

JAMA cardiology
IMPORTANCE: Millions of clinicians rely daily on automated preliminary electrocardiogram (ECG) interpretation. Critical comparisons of machine learning-based automated analysis against clinically accepted standards of care are lacking.

Fully Automated Gross Tumor Volume Delineation From PET in Head and Neck Cancer Using Deep Learning Algorithms.

Clinical nuclear medicine
PURPOSE: The availability of automated, accurate, and robust gross tumor volume (GTV) segmentation algorithms is critical for the management of head and neck cancer (HNC) patients. In this work, we evaluated 3 state-of-the-art deep learning algorithm...