AIMC Topic: Algorithms

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The role of public challenges and data sets towards algorithm development, trust, and use in clinical practice.

Seminars in cutaneous medicine and surgery
In the past decade, machine learning and artificial intelligence have made significant advancements in pattern analysis, including speech and natural language processing, image recognition, object detection, facial recognition, and action categorizat...

Development and Validation of a Deep Learning-Based Automated Detection Algorithm for Major Thoracic Diseases on Chest Radiographs.

JAMA network open
IMPORTANCE: Interpretation of chest radiographs is a challenging task prone to errors, requiring expert readers. An automated system that can accurately classify chest radiographs may help streamline the clinical workflow.

Comparison of Artificial Intelligence Techniques to Evaluate Performance of a Classifier for Automatic Grading of Prostate Cancer From Digitized Histopathologic Images.

JAMA network open
IMPORTANCE: Proper evaluation of the performance of artificial intelligence techniques in the analysis of digitized medical images is paramount for the adoption of such techniques by the medical community and regulatory agencies.

CropDeep: The Crop Vision Dataset for Deep-Learning-Based Classification and Detection in Precision Agriculture.

Sensors (Basel, Switzerland)
Intelligence has been considered as the major challenge in promoting economic potential and production efficiency of precision agriculture. In order to apply advanced deep-learning technology to complete various agricultural tasks in online and offli...

Automated detection of koalas using low-level aerial surveillance and machine learning.

Scientific reports
Effective wildlife management relies on the accurate and precise detection of individual animals. These can be challenging data to collect for many cryptic species, particularly those that live in complex structural environments. This study introduce...

Classifying Biomedical Figures by Modality via Multi-Label Learning.

IEEE journal of biomedical and health informatics
The figures found in biomedical literature are a vital part of biomedical research, education, and clinical decision. The multitude of their modalities and the lack of corresponding metadata constitute search and information, retrieval a difficult ta...

An integrative computational architecture for object-driven cortex.

Current opinion in neurobiology
Computational architecture for object-driven cortex Objects in motion activate multiple cortical regions in every lobe of the human brain. Do these regions represent a collection of independent systems, or is there an overarching functional architect...

U-Net based deep learning bladder segmentation in CT urography.

Medical physics
OBJECTIVES: To develop a U-Net-based deep learning approach (U-DL) for bladder segmentation in computed tomography urography (CTU) as a part of a computer-assisted bladder cancer detection and treatment response assessment pipeline.

[Data-driven integrated diagnostics: the natural evolution of clinical chemistry?].

Nederlands tijdschrift voor geneeskunde
In the near future, making a correct medical diagnosis will be increasingly supported by artificial intelligence. The development of algorithms that integrate all data from an individual into the diagnostic process calls for a multidisciplinary appro...