AIMC Topic: Machine Learning

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Machine learning demonstrates that somatic mutations imprint invariant morphologic features in myelodysplastic syndromes.

Blood
Morphologic interpretation is the standard in diagnosing myelodysplastic syndrome (MDS), but it has limitations, such as varying reliability in pathologic evaluation and lack of integration with genetic data. Somatic events shape morphologic features...

Meta-analysis of voice disorders databases and applied machine learning techniques.

Mathematical biosciences and engineering : MBE
Voice disorders are pathological conditions that directly affect voice production. Computer based diagnosis may play a major role in the early detection and in tracking and even development of efficient pathological speech diagnosis, based on a comp...

[Research on first aid measures based on convolutional neural network recognition human actions].

Zhonghua wei zhong bing ji jiu yi xue
OBJECTIVE: To explore the application of human behavior recognition based on convolutional neural network (CNN) in the new generation of pre-hospital first aid.

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...

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...

Machine learning for direct oxygen saturation and hemoglobin concentration assessment using diffuse reflectance spectroscopy.

Journal of biomedical optics
SIGNIFICANCE: Diffuse reflectance spectroscopy (DRS) is frequently used to assess oxygen saturation and hemoglobin concentration in living tissue. Methods solving the inverse problem may include time-consuming nonlinear optimization or artificial neu...

Reimagining T Staging Through Artificial Intelligence and Machine Learning Image Processing Approaches in Digital Pathology.

JCO clinical cancer informatics
Tumor stage and grade, visually assessed by pathologists from evaluation of pathology images in conjunction with radiographic imaging techniques, have been linked to outcome, progression, and survival for a number of cancers. The gold standard of sta...

Predictive modeling in reproductive medicine: Where will the future of artificial intelligence research take us?

Fertility and sterility
Artificial intelligence (AI) systems have been proposed for reproductive medicine since 1997. Although AI is the main driver of emergent technologies in reproduction, such as robotics, Big Data, and internet of things, it will continue to be the engi...

Precision medicine and artificial intelligence: overview and relevance to reproductive medicine.

Fertility and sterility
Traditionally, new treatments have been developed for the population at large. Recently, large-scale genomic sequencing analyses have revealed tremendous genetic diversity between individuals. In diseases driven by genetic events such as cancer, geno...