Development of antibodies often begins with the assessment and optimization of their physicochemical properties, and their efficient engagement with the target of interest. Decisions at the early optimization stage are critical for the success of the...
Accurate and precise identification of cholelithiasis is essential for saving the lives of millions of people worldwide. Although several computer-aided cholelithiasis diagnosis approaches have been introduced in the literature, their use is limited ...
Thyroid nodules are a common endocrine condition, and accurate differentiation between benign and malignant nodules is essential for making appropriate treatment decisions. Traditional ultrasound-based diagnoses often depend on the expertise of physi...
In prostate cancer (PCa), risk calculators have been proposed, relying on clinical parameters and magnetic resonance imaging (MRI) enable early prediction of clinically significant cancer (CsPCa). The prostate imaging-reporting and data system (PI-RA...
Colorectal cancer (CRC) is the second popular cancer in females and third in males, with an increased number of cases. Pathology diagnoses complemented with predictive and prognostic biomarker information is the first step for personalized treatment....
This paper investigates delivery of encapsulated drug from poly lactic-co-glycolic micro-/nano-particles. Experimental data collected from about 50 papers are analyzed by machine learning algorithms including linear regression, principal component an...
Control of movement is learned and uses error feedback during practice to predict actions for the next movement. We previously showed that augmenting error can enhance learning, but while such findings are encouraging, the methods need to be refined ...
This study uses machine learning (ML) to elucidate the contact relationship between the mandibular third molar (M3M) and the inferior alveolar canal (IAC), leading to three major contributions; (1) The first publicly accessible PR image dataset with ...
Forest fires represent a major risk to both ecosystems and human health that rising frequency of it exacerbates global warming. This study introduces an innovative methodology for detecting forest fires and smoke using an enhanced capsule neural netw...
To develop a deep learning model using transfer learning for automatic detection and segmentation of neck lymph nodes (LNs) in computed tomography (CT) images, the study included 11,013 annotated LNs with a short-axis diameter ≥ 3 mm from 626 head an...
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