AIMC Topic: Reproducibility of Results

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Deep Learning for Classification of Pediatric Otitis Media.

The Laryngoscope
OBJECTIVES/HYPOTHESIS: To create a new strategy for monitoring pediatric otitis media (OM), we developed a brief, reliable, and objective method for automated classification using convolutional neural networks (CNNs) with images from otoscope.

Medical Image Retrieval Using Empirical Mode Decomposition with Deep Convolutional Neural Network.

BioMed research international
Content-based medical image retrieval (CBMIR) systems attempt to search medical image database to narrow the semantic gap in medical image analysis. The efficacy of high-level medical information representation using features is a major challenge in ...

Anomaly Identification during Polymerase Chain Reaction for Detecting SARS-CoV-2 Using Artificial Intelligence Trained from Simulated Data.

Molecules (Basel, Switzerland)
Real-time reverse transcription (RT) PCR is the gold standard for detecting Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), owing to its sensitivity and specificity, thereby meeting the demand for the rising number of cases. The scarcit...

Development and validation of an artificial intelligence system for grading colposcopic impressions and guiding biopsies.

BMC medicine
BACKGROUND: Colposcopy diagnosis and directed biopsy are the key components in cervical cancer screening programs. However, their performance is limited by the requirement for experienced colposcopists. This study aimed to develop and validate a Colp...

Data-driven dose calculation algorithm based on deep U-Net.

Physics in medicine and biology
Accurate and efficient dose calculation is an important prerequisite to ensure the success of radiation therapy. However, all the dose calculation algorithms commonly used in current clinical practice have to compromise between calculation accuracy a...

Comparing feedforward and recurrent neural network architectures with human behavior in artificial grammar learning.

Scientific reports
In recent years artificial neural networks achieved performance close to or better than humans in several domains: tasks that were previously human prerogatives, such as language processing, have witnessed remarkable improvements in state of the art ...

Artificial Intelligence in Thyroid Fine Needle Aspiration Biopsies.

Acta cytologica
BACKGROUND: From cell phones to aerospace, artificial intelligence (AI) has wide-reaching influence in the modern age. In this review, we discuss the application of AI solutions to an equally ubiquitous problem in cytopathology - thyroid fine needle ...

Limitations of Deep Learning Attention Mechanisms in Clinical Research: Empirical Case Study Based on the Korean Diabetic Disease Setting.

Journal of medical Internet research
BACKGROUND: Despite excellent prediction performance, noninterpretability has undermined the value of applying deep-learning algorithms in clinical practice. To overcome this limitation, attention mechanism has been introduced to clinical research as...