![Loading...](https://link.springer.com/static/c4a417b97a76cc2980e3c25e2271af3129e08bbe/images/pdf-preview/spacer.gif)
-
Article
Open AccessFusion of fully integrated analog machine learning classifier with electronic medical records for real-time prediction of sepsis onset
The objective of this work is to develop a fusion artificial intelligence (AI) model that combines patient electronic medical record (EMR) and physiological sensor data to accurately predict early risk of seps...
-
Article
Near-set Based Mucin Segmentation in Histopathology Images for Detecting Mucinous Carcinoma
This paper introducesnear-set based segmentation method for extraction and quantification of mucin regions for detecting mucinouscarcinoma (MC which is a sub type of Invasive ductal carcinoma (IDC)). From hist...
-
Article
Open AccessAn Advanced Deep Learning Approach for Ki-67 Stained Hotspot Detection and Proliferation Rate Scoring for Prognostic Evaluation of Breast Cancer
Being a non-histone protein, Ki-67 is one of the essential biomarkers for the immunohistochemical assessment of proliferation rate in breast cancer screening and grading. The Ki-67 signature is always sensitiv...
-
Chapter and Conference Paper
Histogram Based Thresholding for Automated Nucleus Segmentation Using Breast Imprint Cytology
Breast imprint cytology is a well-recognized technique and provides a magnificent cytological clarity. For imprint cytology slide preparation, tissue samples from the needle taken out to touch and rolled over ...