Weakly supervised instance learning for thyroid malignancy prediction from whole slide cytopathology images

Application of a machine learning algorithm to predict malignancy in thyroid cytopathology

(2020) Danielle D. Elliott Range et al.   CANCER CYTOPATHOLOGY

The Use of Artificial Intelligence (AI) Machine Learning to Determine Myocyte Damage in Cardiac Transplant Acute Cellular Rejection

(2020) C. Glass et al.   JOURNAL OF HEART AND LUNG TRANSPLANTATION

Not-so-supervised: a survey of semi-supervised, multi-instance, and transfer learning in medical image analysis

(2019) Veronika Cheplygina et al.   MEDICAL IMAGE ANALYSIS

Clinical-grade computational pathology using weakly supervised deep learning on whole slide images

(2019) Gabriele Campanella et al.   NATURE MEDICINE

Automated detection and classification of thyroid nodules in ultrasound images using clinical-knowledge-guided convolutional neural networks

(2019) Tianjiao Liu et al.   MEDICAL IMAGE ANALYSIS

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

(2017) Shaoqing Ren et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Computerized cytometry and wavelet analysis of follicular lesions for detecting malignancy: A pilot study in thyroid cytology

(2017) Hayim Gilshtein et al.   SURGERY

A brief introduction to weakly supervised learning

(2017) Zhi-Hua Zhou   National Science Review

Classifying and segmenting microscopy images with deep multiple instance learning

(2016) Oren Z. Kraus et al.   BIOINFORMATICS

Ordinal Regression Methods: Survey and Experimental Study

(2016) Pedro Antonio Gutierrez et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Locality Sensitive Deep Learning for Detection and Classification of Nuclei in Routine Colon Cancer Histology Images

(2016) Korsuk Sirinukunwattana et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis

(2016) Geert Litjens et al.   Scientific Reports

Single- vs. multiple-instance classification

(2015) Ethem Alpaydın et al.   PATTERN RECOGNITION

Implementation of the bethesda system for reporting thyroid cytopathology: Interobserver concordance and reclassification of previously inconclusive aspirates

(2014) Priya Pathak et al.   DIAGNOSTIC CYTOPATHOLOGY

Accurate diagnosis of thyroid follicular lesions from nuclear morphology using supervised learning

(2014) John A. Ozolek et al.   MEDICAL IMAGE ANALYSIS

Computer-aided diagnosis system for classifying benign and malignant thyroid nodules in multi-stained FNAB cytological images

(2013) Balasubramanian Gopinath et al.   AUSTRALASIAN PHYSICAL & ENGINEERING SCIENCES IN MEDICINE

The Clinical and Economic Burden of a Sustained Increase in Thyroid Cancer Incidence

(2013) B. Aschebrook-Kilfoy et al.   CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION

Selective Search for Object Recognition

(2013) J. R. R. Uijlings et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION

Group consensus review minimizes the diagnosis of “follicular lesion of undetermined significance” and improves cytohistologic concordance

(2011) Xin Jing et al.   DIAGNOSTIC CYTOPATHOLOGY

The Bethesda System for Reporting Thyroid Cytopathology

(2009) Edmund S. Cibas et al.   AMERICAN JOURNAL OF CLINICAL PATHOLOGY

Design of a multi-classifier system for discriminating benign from malignant thyroid nodules using routinely H&E-stained cytological images

(2007) Antonis Daskalakis et al.   COMPUTERS IN BIOLOGY AND MEDICINE