BACKGROUND AND OBJECTIVES: Computer-aided diagnosis relies on machine learning algorithms that require filtered and preprocessed data as the input. Aligning the image in the desired direction is an additional manual step in post-processing, commonly ...
Chronic HBV infection, the main cause of liver cirrhosis and hepatocellular carcinoma, has become a global health concern. Machine learning algorithms are particularly adept at analyzing medical phenomenon by capturing complex and nonlinear relations...
Environmental monitoring and assessment
Mar 3, 2021
Evapotranspiration (ET) is one of the most important components of global hydrologic cycle and has significant impacts on energy exchange and climate change. Numerous models have been developed to estimate ET so far; however, great uncertainties in m...
Machine learning, a branch of artificial intelligence, is increasingly used in health research, including nursing and maternal outcomes research. Machine learning algorithms are complex and involve statistics and terminology that are not common in he...
International journal of pharmaceutics
Mar 2, 2021
Capping is the frequently observed mechanical defect in tablets arising from the sub-optimal selection of the formulation composition and their robustness of response toward process parameters. Hence, overcoming capping propensity based on the unders...
This study analyzed the prognostic significance of clinico-pathologic factors, including the number of metastatic lymph nodes (LNs) and lymph node ratio (LNR), in patients with papillary thyroid carcinoma (PTC), and attempted to construct a disease r...
BACKGROUND: This study introduced machine learning approaches to predict newborn's body mass index (BMI) based on ultrasound measures and maternal/delivery information.
BACKGROUND: Non-targeted cytotoxics with anticancer activity are often developed through preclinical stages using response criteria observed in cell lines and xenografts. A panel of the NCI-60 cell lines is frequently the first line to define tumor t...
BACKGROUND: Deep learning contributes to uncovering molecular and cellular processes with highly performant algorithms. Convolutional neural networks have become the state-of-the-art tool to provide accurate and fast image data processing. However, p...
The article summarizes various publications on the application of "learning algorithms" and "artificial neural networks" in psychiatry to describe a dystopian future scenario. The draft of a nosology based on molecular biology is opposed to the ecolo...
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