Essays about: "Breast cancer classification"

Showing result 1 - 5 of 18 essays containing the words Breast cancer classification.

  1. 1. Self-Supervised Learning for Tabular Data: Analysing VIME and introducing Mix Encoder

    University essay from Lunds universitet/Fysiska institutionen

    Author : Max Svensson; [2024]
    Keywords : Machine Learning; Self-supervised learning; AI; Physics; Medicine; Physics and Astronomy;

    Abstract : We introduce Mix Encoder, a novel self-supervised learning framework for deep tabular data models based on Mixup [1]. Mix Encoder uses linear interpolations of samples with associated pretext tasks to form useful pre-trained representations. READ MORE

  3. 2. Uncertainty Quantification in Deep Learning for Breast Cancer Classification in Point-of-Care Ultrasound Imaging

    University essay from Lunds universitet/Matematik LTH

    Author : Marisa Wodrich; [2024]
    Keywords : Uncertainty quantification; Deep learning; Breast cancer classification; Trustworthy AI; Point-of-care ultrasound; Mathematics and Statistics;

    Abstract : Breast cancer is the most common type of cancer worldwide with an estimate of 2.3 million new cases in 2020, and the number one cause of cancer-related deaths in women. READ MORE

  4. 3. Using Generative Adversarial Networks for H&E-to-HER2 Stain Translation in Digital Pathology Images

    University essay from Linköpings universitet/Institutionen för medicinsk teknik

    Author : William Tirmén; [2023]
    Keywords : Machine learning; Artificial intelligence; Digital pathology; Image processing; Generative adversarial networks; Image-to-image translation;

    Abstract : In digital pathology, hematoxylin & eosin (H&E) is a routine stain which is performed on most clinical cases and it often provides clinicians with sufficient information for diagnosis. However, when making decisions on how to guide breast cancer treatment, immunohistochemical staining of human epidermal growth factor 2 (HER2 staining) is also needed. READ MORE

  5. 4. Evaluating Random Forest and k-Nearest Neighbour Algorithms on Real-Life Data Sets

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Atheer Salim; Milad Farahani; [2023]
    Keywords : Random Forest; k-Nearest Neighbour; Evaluation; Machine Learning; Classification; Execution Time; Slumpmässig Skog; k-Närmaste Granne; Utvärdering; Maskininlärning; Klassificiering; Exekveringstid;

    Abstract : Computers can be used to classify various types of data, for example to filter email messages, detect computer viruses, detect diseases, etc. This thesis explores two classification algorithms, random forest and k-nearest neighbour, to understand how accurately and how quickly they classify data. READ MORE

  6. 5. Automated HER2 Scoring of Breast Cancer Tissue using Upconverting Nanoparticle Images

    University essay from Lunds universitet/Matematik LTH

    Author : Adam Belfrage; Alexander Wik; [2022]
    Keywords : HER2-scoring; image analysis; interpretability; digital pathology; computer aided pathology; whole slide imaging; ASCO-guidelines; singular value decomposition; shape models; Bayesian classification; Biology and Life Sciences; Medicine and Health Sciences; Technology and Engineering; Mathematics and Statistics;

    Abstract : Computer aided pathology is becoming more and more of a requirement within pathology due to increased demand of individualised treatments and personalised medicine. Because of the advance of digital pathology in recent years, where a high resolution camera acquire images of microscope slides, pathologists can now assess tissue samples in digital images. READ MORE