AIMC Topic: Algorithms

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Contrastive Similarity Matching for Supervised Learning.

Neural computation
We propose a novel biologically plausible solution to the credit assignment problem motivated by observations in the ventral visual pathway and trained deep neural networks. In both, representations of objects in the same category become progressivel...

[A convolutional neural network based model for assisting pathological diagnoses on thyroid liquid-based cytology].

Zhonghua bing li xue za zhi = Chinese journal of pathology
To develop a convolutional neural network based model for assisting pathological diagnoses on thyroid liquid-based cytology specimens. Seven-hundred thyroid TCT slides were collected, scanned for whole slide imaging (WSI), and divided into training...

Automatic Segmentation in Multiple OCT Layers For Stargardt Disease Characterization Via Deep Learning.

Translational vision science & technology
PURPOSE: This study sought to perform automated segmentation of 11 retinal layers and Stargardt-associated features on spectral-domain optical coherence tomography (SD-OCT) images and to analyze differences between normal eyes and eyes diagnosed with...

Machine learning in medicine: Medical droids, tricorders, and a computer named Hal 9000.

Nephrologie & therapeutique
The usage of artificial intelligence to evaluate histological images was recently explored in many different areas of pathology. Studies focusing on nephropathology demonstrated that algorithms could be trained to identify various structures of the k...

Editorial Commentary: Predicting Satisfaction After Hip Arthroscopy Using Machine Learning: What Do Treadmills and Black Boxes Have to Do With Arthroscopy?

Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
The use of advanced statistical methods and artificial intelligence including machine learning enables researchers to identify preoperative characteristics predictive of patients achieving minimal clinically important differences in health outcomes a...

Evaluation of the efficiency of computerized algorithms to formulate a decision support system for deepbite treatment planning.

American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics
INTRODUCTION: This study aimed to evaluate the efficiency of a newly constructed computer-based decision support system (DSS) on the basis of artificial intelligence technology and designed to plan treatment for patients with a deep overbite.

Videomics: bringing deep learning to diagnostic endoscopy.

Current opinion in otolaryngology & head and neck surgery
PURPOSE OF REVIEW: Machine learning (ML) algorithms have augmented human judgment in various fields of clinical medicine. However, little progress has been made in applying these tools to video-endoscopy. We reviewed the field of video-analysis (here...

Machine Learning for Surgical Phase Recognition: A Systematic Review.

Annals of surgery
OBJECTIVE: To provide an overview of ML models and data streams utilized for automated surgical phase recognition.