Lorraine M. King

According to our database1, Lorraine M. King authored at least 11 papers between 2017 and 2022.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2022
Anomaly Detection of Calcifications in Mammography Based on 11, 000 Negative Cases.
IEEE Trans. Biomed. Eng., 2022

DCIS AI-TIL: Ductal Carcinoma In Situ Tumour Infiltrating Lymphocyte Scoring Using Artificial Intelligence.
Proceedings of the Artificial Intelligence over Infrared Images for Medical Applications and Medical Image Assisted Biomarker Discovery, 2022

Automated Dcis Identification From Multiplex Immunohistochemistry Using Generative Adversarial Networks.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

2021
A new method to accurately identify single nucleotide variants using small FFPE breast samples.
Briefings Bioinform., 2021

2020
Prediction of Upstaged Ductal Carcinoma In Situ Using Forced Labeling and Domain Adaptation.
IEEE Trans. Biomed. Eng., 2020

A multitask deep learning method in simultaneously predicting occult invasive disease in ductal carcinoma in-situ and segmenting microcalcifications in mammography.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020

2019
Malignant microcalcification clusters detection using unsupervised deep autoencoders.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, 2019

2018
Learning better deep features for the prediction of occult invasive disease in ductal carcinoma in situ through transfer learning.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018

Improving classification with forced labeling of other related classes: application to prediction of upstaged ductal carcinoma in situ using mammographic features.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018

2017
Can upstaging of ductal carcinoma in situ be predicted at biopsy by histologic and mammographic features?
Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017

Prediction of occult invasive disease in ductal carcinoma in situ using computer-extracted mammographic features.
Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017


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