AIMC Topic: Deep Learning

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Application of machine intelligence technology in the detection of vaccines and medicines for SARS-CoV-2.

European review for medical and pharmacological sciences
Researchers have found many similarities between the 2003 severe acute respiratory syndrome (SARS) virus and SARS-CoV-19 through existing data that reveal the SARS's cause. Artificial intelligence (AI) learning models can be created to predict drug s...

Rapid tissue oxygenation mapping from snapshot structured-light images with adversarial deep learning.

Journal of biomedical optics
SIGNIFICANCE: Spatial frequency-domain imaging (SFDI) is a powerful technique for mapping tissue oxygen saturation over a wide field of view. However, current SFDI methods either require a sequence of several images with different illumination patter...

Deep learning-level melanoma detection by interpretable machine learning and imaging biomarker cues.

Journal of biomedical optics
SIGNIFICANCE: Melanoma is a deadly cancer that physicians struggle to diagnose early because they lack the knowledge to differentiate benign from malignant lesions. Deep machine learning approaches to image analysis offer promise but lack the transpa...

Deep learning applications to combat the dissemination of COVID-19 disease: a review.

European review for medical and pharmacological sciences
Recent Coronavirus (COVID-19) is one of the respiratory diseases, and it is known as fast infectious ability. This dissemination can be decelerated by diagnosing and quarantining patients with COVID-19 at early stages, thereby saving numerous lives. ...

High signal-to-noise ratio reconstruction of low bit-depth optical coherence tomography using deep learning.

Journal of biomedical optics
SIGNIFICANCE: Reducing the bit depth is an effective approach to lower the cost of an optical coherence tomography (OCT) imaging device and increase the transmission efficiency in data acquisition and telemedicine. However, a low bit depth will lead ...

Evaluating predictive models in reproductive medicine.

Fertility and sterility
Predictive modeling has become a distinct subdiscipline of reproductive medicine, and researchers and clinicians are just learning the skills and expertise to evaluate artificial intelligence (AI) studies. Diagnostic tests and model predictions are s...

Holographic Declarative Memory: Distributional Semantics as the Architecture of Memory.

Cognitive science
We demonstrate that the key components of cognitive architectures (declarative and procedural memory) and their key capabilities (learning, memory retrieval, probability judgment, and utility estimation) can be implemented as algebraic operations on ...

Expert-level segmentation using deep learning for volumetry of polycystic kidney and liver.

Investigative and clinical urology
PURPOSE: Volumetry is used in polycystic kidney and liver diseases (PKLDs), including autosomal dominant polycystic kidney disease (ADPKD), to assess disease progression and drug efficiency. However, since no rapid and accurate method for volumetry h...