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Lisa Rydén

Professor Surgery

Umeå Universitet Medicinska fakulteten

Sweden

Research Interests

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Professors in Sweden Professors in Medical Imaging Medical Imaging professors in Sweden

About

Lisa Rydén is a Professor of Surgery at Lunds universitet Medicinska fakulteten in Sweden. Her research focuses on breast cancer, specifically in areas such as predictive modeling, lymph node metastasis, and the health-related quality of life of patients. Recent publications include studies on resection margins, deep learning applications in mammography, and the role of resilience in breast cancer patients.

Articles (36)

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Collaborators (45)

Johan Vallon-Christersson

Lund University

SWEDEN

Lisa Rydén

Research Interests

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About

Articles (36)

Omission of axillary lymph node dissection in ultrasound-detectable axillary metastases in primary breast cancer treated by upfront surgery: prospective randomized SENOMAC-ULTRA non-inferiority trial

Statin use and risk of contralateral breast cancer

Serum Levels of Thyroid Hormones in Relation to Breast Cancer Prognosis: A Multicentre Cohort Study.

Multiomic profiling of ER-positive HER2-negative breast cancer reveals markers associated with metastatic spread

Multimodal Gene Expression Deep Learning for Predicting Sentinel Lymph Node Macro-metastasis in Early Breast Cancer: Development and Validation in the SCAN-B Cohort

Human factors validation study of an artificial neural network‑based preoperative decision‑support tool for noninvasive lymph node staging (NILS) in women with primary breast cancer (ISRCTN99301435)

Association between shoulder joint radiation dose and arm morbidity in the randomized breast cancer trial SENOMAC

NeoCircle

Statin use and risk of breast cancer among women with benign breast disease

Development and validation of prediction models for sentinel lymph node status indicating postmastectomy radiotherapy in breast cancer: population-based study

External validation of a multivariable prediction model for positive resection margins in breast-conserving surgery

Experiences of rehabilitation one year after breast cancer diagnosis–A focus group study from the ReScreen randomized controlled trial

Omitting completion axillary lymph node dissection in breast cancer patients with sentinel lymph node micrometastases undergoing mastectomy: results from the prospective SENOMIC trial

Deep learning on routine full-breast mammograms enhances lymph node metastasis prediction in early breast cancer

Prognostic relevance of CD163+ immune cells in patients with metastatic breast cancer

Myeloperoxidase expressing tumor associated neutrophils are associated with worse prognosis in metastatic breast cancer patients

Prediction of sentinel lymph node status in patients with early breast cancer using breast imaging as an alternative to surgical staging—a systematic review and meta-analysis

Multilayered Epigenetic Analysis Identifies a Molecular Portrait for Psychological Resilience in Patients With Breast Cancer

Health-related quality of life by type of breast surgery in women with primary breast cancer: prospective longitudinal cohort study

Hormone receptor mRNA and protein levels as predictors of premenopausal tamoxifen benefit

Retrospective validation study of an artificial neural network-based preoperative decision-support tool for noninvasive lymph node staging (NILS) in women with primary breast cancer (ISRCTN14341750)

Axillary clearance and chemotherapy rates in ER+HER2− breast cancer

Model of Health-Related Quality of Life in Breast Cancer Patients Using Cross-Sectional Data: The Role of Resilience

Prediction of High Nodal Burden in Patients With Sentinel Node-Positive Luminal ERBB2-Negative Breast Cancer.

Risk-adjusted benchmarking of long-term overall survival in patients with HER2-positive early-stage Breast cancer: A Swedish retrospective cohort study

A prospective cohort study identifying radiologic and tumor related factors of importance for breast conserving surgery after neoadjuvant chemotherapy

Breast Cancer Diagnosis Using Extended-Wavelength–Diffuse Reflectance Spectroscopy (EW-DRS)—Proof of Concept in Ex Vivo Breast Specimens Using Machine Learning

Noninvasive Staging of Lymph Node Status in Breast Cancer Using Machine Learning: External Validation and Further Model Development

Choice of High-Throughput Proteomics Method Affects Data Integration with Transcriptomics and the Potential Use in Biomarker Discovery

How Reliable Are Gene Expression-Based and Immunohistochemical Biomarkers Assessed on a Core-Needle Biopsy? A Study of Paired Core-Needle Biopsies and Surgical Specimens in Early Breast Cancer

The implementation of a noninvasive lymph node staging (NILS) preoperative prediction model is cost effective in primary breast cancer

Peripheral Blood Mononuclear Cell Populations Correlate with Outcome in Patients with Metastatic Breast Cancer

PAM50 subtyping and ROR score add long-term prognostic information in premenopausal breast cancer patients

Feasibility and Relevance of an Intervention with Systematic Screening as a Base for Individualized Rehabilitation in Breast Cancer Patients: A Pilot Trial of the ReScreen Randomized Controlled Trial

The NILS Study Protocol: A Retrospective Validation Study of an Artificial Neural Network Based Preoperative Decision-Making Tool for Noninvasive Lymph Node Staging in Women with Primary Breast Cancer (ISRCTN14341750)

The Prognostic Role of Intratumoral Stromal Content in Lobular Breast Cancer

Collaborators (45)

Johan Vallon-Christersson

Nina Reistad

Jakob Hansen Viuff

Ylva Bengtsson

Ulrika Olsson Möller

Ingrid Hedenfalk

Signe Borgquist

Marlene Malmström

Tove Filtenborg Tvedskov

Anna Ehinger

Ida Skarping

Magnus Dustler

Lutz Schomburg

Magnus Cinthio

Kim Gulis

Carl Borrebaeck

Sophia Zackrisson

Julia Tutzauer

Maria Margarete Karsten

Mårten Fernö

Tuomo Meretoja

Peer Christiansen

Lao Saal

Maria Ekholm

Patrik Edén

Stephen Nash

Irina Palimaru Manhoobi

Helena Sackey

Kamil Demircan

Elham Hedayati

Mattias Ohlsson

Malin Sund

Caroline Bergenfelz

Fredrik Levander

Deirdre Cronin-Fenton

Heena Dalal

Katarina Steen Carlsson