AI Medical Compendium Topic:
Databases, Factual

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MetaAge: Meta-Learning Personalized Age Estimators.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Different people age in different ways. Learning a personalized age estimator for each person is a promising direction for age estimation given that it better models the personalization of aging processes. However, most existing personalized methods ...

Data governance functions to support responsible data stewardship in pediatric radiology research studies using artificial intelligence.

Pediatric radiology
The integration of human and machine intelligence promises to profoundly change the practice of medicine. The rapidly increasing adoption of artificial intelligence (AI) solutions highlights its potential to streamline physician work and optimize cli...

Deep Learning-driven classification of external DICOM studies for PACS archiving.

European radiology
OBJECTIVES: Over the course of their treatment, patients often switch hospitals, requiring staff at the new hospital to import external imaging studies to their local database. In this study, the authors present MOdality Mapping and Orchestration (MO...

Machine learning for improving high-dimensional proxy confounder adjustment in healthcare database studies: An overview of the current literature.

Pharmacoepidemiology and drug safety
PURPOSE: Supplementing investigator-specified variables with large numbers of empirically identified features that collectively serve as 'proxies' for unspecified or unmeasured factors can often improve confounding control in studies utilizing admini...

A Modified Deep Learning Framework for Arrhythmia Disease Analysis in Medical Imaging Using Electrocardiogram Signal.

BioMed research international
Arrhythmias are anomalies in the heartbeat rhythm that occur occasionally in people's lives. These arrhythmias can lead to potentially deadly consequences, putting your life in jeopardy. As a result, arrhythmia identification and classification are a...

Segmentation of laser induced retinal lesions using deep learning (December 2021).

Lasers in surgery and medicine
OBJECTIVE: Detection of retinal laser lesions is necessary in both the evaluation of the extent of damage from high power laser sources, and in validating treatments involving the placement of laser lesions. However, such lesions are difficult to det...

Machine Learning for Renal Pathologies: An Updated Survey.

Sensors (Basel, Switzerland)
Within the literature concerning modern machine learning techniques applied to the medical field, there is a growing interest in the application of these technologies to the nephrological area, especially regarding the study of renal pathologies, bec...

Research on Sports Health Care Information System Based on Computer Deep Learning Algorithm.

Computational intelligence and neuroscience
There are various problems in diagnosing and treating tumor diseases in significant hospitals. The content includes misjudgement and over-surgery issues. For example, the judgment of pulmonary nodules mainly relies on artificial experience, and most ...

A Systematic Review of Wi-Fi and Machine Learning Integration with Topic Modeling Techniques.

Sensors (Basel, Switzerland)
Wireless networks have drastically influenced our lifestyle, changing our workplaces and society. Among the variety of wireless technology, Wi-Fi surely plays a leading role, especially in local area networks. The spread of mobiles and tablets, and m...

Analysis of Data Interaction Process Based on Data Mining and Neural Network Topology Visualization.

Computational intelligence and neuroscience
This paper addresses data mining and neural network model construction and analysis to design a data interaction process model based on data mining and topology visualization. This paper performs preprocessing data operations such as data filtering a...