AIMC Topic: Artificial Intelligence

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Vegetable Size Measurement Based on Stereo Camera and Keypoints Detection.

Sensors (Basel, Switzerland)
This work focuses on the problem of non-contact measurement for vegetables in agricultural automation. The application of computer vision in assisted agricultural production significantly improves work efficiency due to the rapid development of infor...

From shallow to deep: some lessons learned from application of machine learning for recognition of functional genomic elements in human genome.

Human genomics
Identification of genomic signals as indicators for functional genomic elements is one of the areas that received early and widespread application of machine learning methods. With time, the methods applied grew in variety and generally exhibited a t...

Automatic Building Extraction on Satellite Images Using Unet and ResNet50.

Computational intelligence and neuroscience
Recently, settlement planning and replanning process are becoming the main problem in rapidly growing cities. Unplanned urban settlements are quite common, especially in low-income countries. Building extraction on satellite images poses another prob...

Deploying Machine Learning Models Using Progressive Web Applications: Implementation Using a Neural Network Prediction Model for Pneumonia Related Child Mortality in The Gambia.

Frontiers in public health
BACKGROUND: Translating research outputs into practical tools for medical practitioners is a neglected area and could have a substantial impact. One of the barriers to implementing artificial intelligence (AI) and machine learning (ML) applications i...

Interpretable tumor differentiation grade and microsatellite instability recognition in gastric cancer using deep learning.

Laboratory investigation; a journal of technical methods and pathology
Gastric cancer possesses great histological and molecular diversity, which creates obstacles for rapid and efficient diagnoses. Classic diagnoses either depend on the pathologist's judgment, which relies heavily on subjective experience, or time-cons...

The importance of multi-modal imaging and clinical information for humans and AI-based algorithms to classify breast masses (INSPiRED 003): an international, multicenter analysis.

European radiology
OBJECTIVES: AI-based algorithms for medical image analysis showed comparable performance to human image readers. However, in practice, diagnoses are made using multiple imaging modalities alongside other data sources. We determined the importance of ...

The ethical challenges of artificial intelligence-driven digital pathology.

The journal of pathology. Clinical research
Digital pathology - the digitalisation of clinical histopathology services through the scanning and storage of pathology slides - has opened up new possibilities for health care in recent years, particularly in the opportunities it brings for artific...

[The analysis of CIRSmedical.de using Natural Language Processing].

Zeitschrift fur Evidenz, Fortbildung und Qualitat im Gesundheitswesen
BACKGROUND: CIRSmedical.de is a publicly accessible, cross-institutional reporting and learning system, which is organized by the German Agency for Quality in Medicine (ÄZQ). CIRSmedical.de has existed since 2005 and has published more than 6,000 eve...

Assessment and validation of a novel fast fully automated artificial intelligence left ventricular ejection fraction quantification software.

Echocardiography (Mount Kisco, N.Y.)
BACKGROUND: Quantification of left ventricular ejection fraction (LVEF) by transthoracic echocardiography (TTE) is operator-dependent, time-consuming, and error-prone. LVivoEF by DIA is a new artificial intelligence (AI) software, which displays the ...