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Eliminating the breast cancer surgery paradigm after neoadjuvant systemic therapy: current evidence and future challenges

Annals of oncology, 2020-01, Vol.31 (1), p.61-71

2020

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Patients should be the tipping point of individualizing breast cancer surgery: Commentary on ‘Eliminating the breast cancer surgery paradigm after neoadjuvant systemic therapy: current evidence and future challenges’

Annals of oncology, 2020-09, Vol.31 (9), p.1264-1264

2020

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The CINDERELLA APProach: Future Concepts for Patient Empowerment in Breast Cancer Treatment with Artificial Intelligence-Driven Healthcare Platform

European journal of cancer (1990), 2024-03, Vol.200, p.113784, Article 113784

2024

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69P Use of bevacizumab for patients with FIGO stage IIIB to IV epithelial ovarian cancer undergoing primary debulking surgery and its association with oncologic outcomes: A German cancer registry study

ESMO open, 2024-06, Vol.9, p.103576, Article 103576

2024

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97P The impact of updated imaging software on the performance of machine learning models for breast cancer diagnosis: A multi-center, retrospective study

ESMO open, 2024-05, Vol.9, p.103168, Article 103168

2024

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140P Use of chemotherapy and loco-regional therapy for stage IA triple-negative breast cancer and their association with oncologic outcomes: A cancer registry study

ESMO open, 2024-05, Vol.9, p.103127, Article 103127

2024

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169P Radiomics models for B-mode breast ultrasound and strain elastography for breast cancer diagnosis (INSPiRED 005): An international, multicenter analysis

ESMO open, 2024-05, Vol.9, p.103191, Article 103191

2024

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147P Racial bias in pretreatment MRI radiomics features to predict response to neoadjuvant systemic treatment in breast cancer: A multicenter study in China, Germany, and the US

ESMO open, 2024-05, Vol.9, p.103134, Article 103134

2024

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The Lucerne Toolbox 2 to optimise axillary management for early breast cancer: a multidisciplinary expert consensus

EClinicalMedicine, 2023-07, Vol.61, p.102085-102085, Article 102085

2023

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108TiP CINDERELLA clinical trial: Using artificial intelligence-driven healthcare to enhance breast cancer locoregional treatment decisions

ESMO open, 2024-05, Vol.9, p.103179, Article 103179

2024

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Towards data-driven decision-making for breast cancer patients undergoing mastectomy and reconstruction: accurate prediction of individual patient-reported outcomes at 2-year follow-up using machine learning

Geburtshilfe und Frauenheilkunde, 2020, Vol.80 (10)

2020

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Artificial intelligence to accurately identify and select breast cancer patients with a pathologic complete response for omission of surgery after neoadjuvant systemic therapy: an international multicenter analysis

Geburtshilfe und Frauenheilkunde, 2020, Vol.80 (10)

2020

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Aortic regurgitant flow by color Doppler measurement of the local velocity 7 mm above the leak orifice: Part 1: in vitro measurements

Clinical research in cardiology, 1999-09, Vol.88 (9), p.631-639

1999

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3-D Cholangiographie und digitale ERCP – Optimierte Konkrementdetektion bei Choledocholithiasis oder Spielerei?

Zeitschrift für Gastroenterologie, 2007, Vol.45 (8)

2007

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Influence of pulse repetition frequency and high pass filter on color Doppler maps of converging flow in vitro

International journal of cardiac imaging, 1996-12, Vol.12 (4), p.257-261

1996

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Submuköse Raumforderung im distalen Ösophagus

Gastroenterologe, 2012-03, Vol.7 (2), p.127-129

2012

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Farbdoppler-Echokardiographie der Flusskonvergenzregion in vitro : Einfluss der Lochform auf das proximale Geschwindigkeitsprofil

Zeitschrift für Kardiologie, 1996, Vol.85 (1), p.45-52

1996

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ber Nitrosoproducte der Mono ther des Brenzcatechins

Monatshefte für Chemie, 1897-12, Vol.18 (1), p.467-480

Pfob, A.

1897

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Color Doppler echocardiography of the flow convergence region in vitro: effect of the orifice shape on proximal velocity profile

Zeitschrift für Kardiologie, 1996-01, Vol.85 (1), p.45-52

1996

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The underused potential of breast conserving therapy after neoadjuvant system treatment – Causes and solutions

Breast (Edinburgh), 2023-02, Vol.67, p.110-115

2023

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Artificial intelligence to de-escalate loco-regional breast cancer treatment

Breast (Edinburgh), 2023-04, Vol.68, p.201-204

2023

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Breast elastography—ready for prime time?

European radiology, 2024-02, Vol.34 (2), p.943-944

2024

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Breast and axillary surgery after neoadjuvant systemic treatment – A review of clinical routine recommendations and the latest clinical research

Breast (Edinburgh), 2022-03, Vol.62 (Suppl 1), p.S7-S11

2022

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Machine learning in medicine: a practical introduction to techniques for data pre-processing, hyperparameter tuning, and model comparison

BMC medical research methodology, 2022-11, Vol.22 (1), p.1-282, Article 282

2022

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De-escalation of breast and axillary surgery in exceptional responders to neoadjuvant systemic treatment

The lancet oncology, 2021-04, Vol.22 (4), p.435-436

2021

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Eliminating the breast cancer surgery paradigm after neoadjuvant systemic therapy: current evidence and future challenges

Patients should be the tipping point of individualizing breast cancer surgery: Commentary on ‘Eliminating the breast cancer surgery paradigm after neoadjuvant systemic therapy: current evidence and future challenges’

The CINDERELLA APProach: Future Concepts for Patient Empowerment in Breast Cancer Treatment with Artificial Intelligence-Driven Healthcare Platform

69P Use of bevacizumab for patients with FIGO stage IIIB to IV epithelial ovarian cancer undergoing primary debulking surgery and its association with oncologic outcomes: A German cancer registry study

97P The impact of updated imaging software on the performance of machine learning models for breast cancer diagnosis: A multi-center, retrospective study

140P Use of chemotherapy and loco-regional therapy for stage IA triple-negative breast cancer and their association with oncologic outcomes: A cancer registry study

169P Radiomics models for B-mode breast ultrasound and strain elastography for breast cancer diagnosis (INSPiRED 005): An international, multicenter analysis

147P Racial bias in pretreatment MRI radiomics features to predict response to neoadjuvant systemic treatment in breast cancer: A multicenter study in China, Germany, and the US

The Lucerne Toolbox 2 to optimise axillary management for early breast cancer: a multidisciplinary expert consensus

108TiP CINDERELLA clinical trial: Using artificial intelligence-driven healthcare to enhance breast cancer locoregional treatment decisions

Towards data-driven decision-making for breast cancer patients undergoing mastectomy and reconstruction: accurate prediction of individual patient-reported outcomes at 2-year follow-up using machine learning

Artificial intelligence to accurately identify and select breast cancer patients with a pathologic complete response for omission of surgery after neoadjuvant systemic therapy: an international multicenter analysis

Aortic regurgitant flow by color Doppler measurement of the local velocity 7 mm above the leak orifice: Part 1: in vitro measurements

3-D Cholangiographie und digitale ERCP – Optimierte Konkrementdetektion bei Choledocholithiasis oder Spielerei?

Influence of pulse repetition frequency and high pass filter on color Doppler maps of converging flow in vitro

Submuköse Raumforderung im distalen Ösophagus

Farbdoppler-Echokardiographie der Flusskonvergenzregion in vitro : Einfluss der Lochform auf das proximale Geschwindigkeitsprofil

ber Nitrosoproducte der Mono ther des Brenzcatechins

Color Doppler echocardiography of the flow convergence region in vitro: effect of the orifice shape on proximal velocity profile

The underused potential of breast conserving therapy after neoadjuvant system treatment – Causes and solutions

Artificial intelligence to de-escalate loco-regional breast cancer treatment

Breast elastography—ready for prime time?

Breast and axillary surgery after neoadjuvant systemic treatment – A review of clinical routine recommendations and the latest clinical research

Machine learning in medicine: a practical introduction to techniques for data pre-processing, hyperparameter tuning, and model comparison

De-escalation of breast and axillary surgery in exceptional responders to neoadjuvant systemic treatment

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