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Related papers: Longitudinal Mammogram Risk Prediction

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Breast cancer is the most commonly occurring cancer worldwide. This cancer caused 670,000 deaths globally in 2022, as reported by the WHO. Yet since health officials began routine mammography screening in age groups deemed at risk in the…

Computer Vision and Pattern Recognition · Computer Science 2025-06-17 Mahmudul Hasan

Cancer is one of the diseases that kill the most women in the world, with breast cancer being responsible for the highest number of cancer cases and consequently deaths. However, it can be prevented by early detection and, consequently,…

Machine Learning · Computer Science 2025-09-23 João Manoel Herrera Pinheiro , Marcelo Becker

Brain tumor is a life-threatening problem and hampers the normal functioning of the human body. The average five-year relative survival rate for malignant brain tumors is 35.6 percent. For proper diagnosis and efficient treatment planning,…

Image and Video Processing · Electrical Eng. & Systems 2024-07-16 Vidhyapriya Ranganathan , Celshiya Udaiyar , Jaisree Jayanth , Meghaa P , Srija B , Uthra S

Breast cancer presents the second largest cancer risk in the world to women. Early detection of cancer has been shown to be effective in reducing mortality. Population screening programs schedule regular mammography imaging for…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Edward Kendall , Paraham Hajishafiezahramini , Matthew Hamilton , Gregory Doyle , Nancy Wadden , Oscar Meruvia-Pastor

Early detection of breast cancer is critical for improving patient outcomes. While mammography remains the primary screening modality, magnetic resonance imaging (MRI) is increasingly recommended as a supplemental tool for women with dense…

This study enhances breast cancer prediction by using large language models to infer the likelihood of confounding diseases, namely diabetes, obesity, and cardiovascular disease, from routine clinical data. These AI-generated features…

Machine Learning · Computer Science 2025-11-25 Debmita Roy

Predicting breast cancer recurrence risk is a critical clinical challenge. This study investigates the potential of computational pathology to stratify patients using deep learning on routine Hematoxylin and Eosin (H&E) stained whole-slide…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Jinqiu Chen , Huyan Xu

Lung cancer remains one of the leading causes of morbidity and mortality worldwide, making early diagnosis critical for improving therapeutic outcomes and patient prognosis. Computer-aided diagnosis systems, which analyze computed…

Image and Video Processing · Electrical Eng. & Systems 2025-06-23 Guohui Cai , Ying Cai , Zeyu Zhang , Yuanzhouhan Cao , Lin Wu , Daji Ergu , Zhinbin Liao , Yang Zhao

Lung cancer is the leading cause of death among different types of cancers. Every year, the lives lost due to lung cancer exceed those lost to pancreatic, breast, and prostate cancer combined. The survival rate for lung cancer patients is…

Image and Video Processing · Electrical Eng. & Systems 2023-02-17 Saleh Abunajm , Nelly Elsayed , Zag ElSayed , Murat Ozer

Early diagnosis of breast cancer (BC) significantly contributes to reducing the mortality rate worldwide. The detection of different factors and biomarkers such as Estrogen receptor (ER), Progesterone receptor (PR), Human epidermal growth…

Image and Video Processing · Electrical Eng. & Systems 2024-09-18 Abdul Rehman , Sarfaraz Hussein , Waqas Sultani

The Deep learning (DL) models for diagnosing breast cancer from mammographic images often operate as "black boxes", making it difficult for healthcare professionals to trust and understand their decision-making processes. The study presents…

Computer Vision and Pattern Recognition · Computer Science 2024-04-30 Maryam Ahmed , Tooba Bibi , Rizwan Ahmed Khan , Sidra Nasir

Abstract Cancer is a tumor that affects people worldwide, with a higher incidence in females but not excluding males. It ranks among the top five deadliest types of cancer, particularly prevalent in less developed countries with deficient…

Precise estimation of cardiac patients' current and future comorbidities is an important factor in prioritizing continuous physiological monitoring and new therapies. ML models have shown satisfactory performance in short-term mortality…

Machine Learning · Computer Science 2024-03-05 Bijan Roudini , Boshra Khajehpiri , Hamid Abrishami Moghaddam , Mohamad Forouzanfar

With an estimated 160,000 deaths in 2018, lung cancer is the most common cause of cancer death in the United States. Lung cancer CT screening has been shown to reduce mortality by up to 40% and is now included in US screening guidelines.…

Image and Video Processing · Electrical Eng. & Systems 2020-07-28 Daniel Korat

Breast cancer is the most commonly diagnosed cancer and the leading cause of cancer-related mortality in women globally. Mammography is essential for the early detection and diagnosis of breast lesions. Despite recent progress in foundation…

Computer-aided detection systems based on deep learning have shown good performance in breast cancer detection. However, high-density breasts show poorer detection performance since dense tissues can mask or even simulate masses. Therefore,…

Image and Video Processing · Electrical Eng. & Systems 2023-01-25 Lidia Garrucho , Kaisar Kushibar , Richard Osuala , Oliver Diaz , Alessandro Catanese , Javier del Riego , Maciej Bobowicz , Fredrik Strand , Laura Igual , Karim Lekadir

Risk prediction is central to both clinical medicine and public health. While many machine learning models have been developed to predict mortality, they are rarely applied in the clinical literature, where classification tasks typically…

Machine Learning · Statistics 2017-12-05 Maggie Makar , Marzyeh Ghassemi , David Cutler , Ziad Obermeyer

Large-scale biobanks are being collected around the world in efforts to better understand human health and risk factors for disease. They often survey hundreds of thousands of individuals, combining questionnaires with clinical, genetic,…

Quantitative Methods · Quantitative Biology 2019-03-19 Qifan Yang , Gennady V. Roshchupkin , Wiro J. Niessen , Sarah E. Medland , Alyssa H. Zhu , Paul M. Thompson , Neda Jahanshad

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and…

Computer Vision and Pattern Recognition · Computer Science 2019-04-24 Spyridon Bakas , Mauricio Reyes , Andras Jakab , Stefan Bauer , Markus Rempfler , Alessandro Crimi , Russell Takeshi Shinohara , Christoph Berger , Sung Min Ha , Martin Rozycki , Marcel Prastawa , Esther Alberts , Jana Lipkova , John Freymann , Justin Kirby , Michel Bilello , Hassan Fathallah-Shaykh , Roland Wiest , Jan Kirschke , Benedikt Wiestler , Rivka Colen , Aikaterini Kotrotsou , Pamela Lamontagne , Daniel Marcus , Mikhail Milchenko , Arash Nazeri , Marc-Andre Weber , Abhishek Mahajan , Ujjwal Baid , Elizabeth Gerstner , Dongjin Kwon , Gagan Acharya , Manu Agarwal , Mahbubul Alam , Alberto Albiol , Antonio Albiol , Francisco J. Albiol , Varghese Alex , Nigel Allinson , Pedro H. A. Amorim , Abhijit Amrutkar , Ganesh Anand , Simon Andermatt , Tal Arbel , Pablo Arbelaez , Aaron Avery , Muneeza Azmat , Pranjal B. , W Bai , Subhashis Banerjee , Bill Barth , Thomas Batchelder , Kayhan Batmanghelich , Enzo Battistella , Andrew Beers , Mikhail Belyaev , Martin Bendszus , Eze Benson , Jose Bernal , Halandur Nagaraja Bharath , George Biros , Sotirios Bisdas , James Brown , Mariano Cabezas , Shilei Cao , Jorge M. Cardoso , Eric N Carver , Adrià Casamitjana , Laura Silvana Castillo , Marcel Catà , Philippe Cattin , Albert Cerigues , Vinicius S. Chagas , Siddhartha Chandra , Yi-Ju Chang , Shiyu Chang , Ken Chang , Joseph Chazalon , Shengcong Chen , Wei Chen , Jefferson W Chen , Zhaolin Chen , Kun Cheng , Ahana Roy Choudhury , Roger Chylla , Albert Clérigues , Steven Colleman , Ramiro German Rodriguez Colmeiro , Marc Combalia , Anthony Costa , Xiaomeng Cui , Zhenzhen Dai , Lutao Dai , Laura Alexandra Daza , Eric Deutsch , Changxing Ding , Chao Dong , Shidu Dong , Wojciech Dudzik , Zach Eaton-Rosen , Gary Egan , Guilherme Escudero , Théo Estienne , Richard Everson , Jonathan Fabrizio , Yong Fan , Longwei Fang , Xue Feng , Enzo Ferrante , Lucas Fidon , Martin Fischer , Andrew P. French , Naomi Fridman , Huan Fu , David Fuentes , Yaozong Gao , Evan Gates , David Gering , Amir Gholami , Willi Gierke , Ben Glocker , Mingming Gong , Sandra González-Villá , T. Grosges , Yuanfang Guan , Sheng Guo , Sudeep Gupta , Woo-Sup Han , Il Song Han , Konstantin Harmuth , Huiguang He , Aura Hernández-Sabaté , Evelyn Herrmann , Naveen Himthani , Winston Hsu , Cheyu Hsu , Xiaojun Hu , Xiaobin Hu , Yan Hu , Yifan Hu , Rui Hua , Teng-Yi Huang , Weilin Huang , Sabine Van Huffel , Quan Huo , Vivek HV , Khan M. Iftekharuddin , Fabian Isensee , Mobarakol Islam , Aaron S. Jackson , Sachin R. Jambawalikar , Andrew Jesson , Weijian Jian , Peter Jin , V Jeya Maria Jose , Alain Jungo , B Kainz , Konstantinos Kamnitsas , Po-Yu Kao , Ayush Karnawat , Thomas Kellermeier , Adel Kermi , Kurt Keutzer , Mohamed Tarek Khadir , Mahendra Khened , Philipp Kickingereder , Geena Kim , Nik King , Haley Knapp , Urspeter Knecht , Lisa Kohli , Deren Kong , Xiangmao Kong , Simon Koppers , Avinash Kori , Ganapathy Krishnamurthi , Egor Krivov , Piyush Kumar , Kaisar Kushibar , Dmitrii Lachinov , Tryphon Lambrou , Joon Lee , Chengen Lee , Yuehchou Lee , M Lee , Szidonia Lefkovits , Laszlo Lefkovits , James Levitt , Tengfei Li , Hongwei Li , Wenqi Li , Hongyang Li , Xiaochuan Li , Yuexiang Li , Heng Li , Zhenye Li , Xiaoyu Li , Zeju Li , XiaoGang Li , Wenqi Li , Zheng-Shen Lin , Fengming Lin , Pietro Lio , Chang Liu , Boqiang Liu , Xiang Liu , Mingyuan Liu , Ju Liu , Luyan Liu , Xavier Llado , Marc Moreno Lopez , Pablo Ribalta Lorenzo , Zhentai Lu , Lin Luo , Zhigang Luo , Jun Ma , Kai Ma , Thomas Mackie , Anant Madabushi , Issam Mahmoudi , Klaus H. Maier-Hein , Pradipta Maji , CP Mammen , Andreas Mang , B. S. Manjunath , Michal Marcinkiewicz , S McDonagh , Stephen McKenna , Richard McKinley , Miriam Mehl , Sachin Mehta , Raghav Mehta , Raphael Meier , Christoph Meinel , Dorit Merhof , Craig Meyer , Robert Miller , Sushmita Mitra , Aliasgar Moiyadi , David Molina-Garcia , Miguel A. B. Monteiro , Grzegorz Mrukwa , Andriy Myronenko , Jakub Nalepa , Thuyen Ngo , Dong Nie , Holly Ning , Chen Niu , Nicholas K Nuechterlein , Eric Oermann , Arlindo Oliveira , Diego D. C. Oliveira , Arnau Oliver , Alexander F. I. Osman , Yu-Nian Ou , Sebastien Ourselin , Nikos Paragios , Moo Sung Park , Brad Paschke , J. Gregory Pauloski , Kamlesh Pawar , Nick Pawlowski , Linmin Pei , Suting Peng , Silvio M. Pereira , Julian Perez-Beteta , Victor M. Perez-Garcia , Simon Pezold , Bao Pham , Ashish Phophalia , Gemma Piella , G. N. Pillai , Marie Piraud , Maxim Pisov , Anmol Popli , Michael P. Pound , Reza Pourreza , Prateek Prasanna , Vesna Prkovska , Tony P. Pridmore , Santi Puch , Élodie Puybareau , Buyue Qian , Xu Qiao , Martin Rajchl , Swapnil Rane , Michael Rebsamen , Hongliang Ren , Xuhua Ren , Karthik Revanuru , Mina Rezaei , Oliver Rippel , Luis Carlos Rivera , Charlotte Robert , Bruce Rosen , Daniel Rueckert , Mohammed Safwan , Mostafa Salem , Joaquim Salvi , Irina Sanchez , Irina Sánchez , Heitor M. Santos , Emmett Sartor , Dawid Schellingerhout , Klaudius Scheufele , Matthew R. Scott , Artur A. Scussel , Sara Sedlar , Juan Pablo Serrano-Rubio , N. Jon Shah , Nameetha Shah , Mazhar Shaikh , B. Uma Shankar , Zeina Shboul , Haipeng Shen , Dinggang Shen , Linlin Shen , Haocheng Shen , Varun Shenoy , Feng Shi , Hyung Eun Shin , Hai Shu , Diana Sima , M Sinclair , Orjan Smedby , James M. Snyder , Mohammadreza Soltaninejad , Guidong Song , Mehul Soni , Jean Stawiaski , Shashank Subramanian , Li Sun , Roger Sun , Jiawei Sun , Kay Sun , Yu Sun , Guoxia Sun , Shuang Sun , Yannick R Suter , Laszlo Szilagyi , Sanjay Talbar , Dacheng Tao , Dacheng Tao , Zhongzhao Teng , Siddhesh Thakur , Meenakshi H Thakur , Sameer Tharakan , Pallavi Tiwari , Guillaume Tochon , Tuan Tran , Yuhsiang M. Tsai , Kuan-Lun Tseng , Tran Anh Tuan , Vadim Turlapov , Nicholas Tustison , Maria Vakalopoulou , Sergi Valverde , Rami Vanguri , Evgeny Vasiliev , Jonathan Ventura , Luis Vera , Tom Vercauteren , C. A. Verrastro , Lasitha Vidyaratne , Veronica Vilaplana , Ajeet Vivekanandan , Guotai Wang , Qian Wang , Chiatse J. Wang , Weichung Wang , Duo Wang , Ruixuan Wang , Yuanyuan Wang , Chunliang Wang , Guotai Wang , Ning Wen , Xin Wen , Leon Weninger , Wolfgang Wick , Shaocheng Wu , Qiang Wu , Yihong Wu , Yong Xia , Yanwu Xu , Xiaowen Xu , Peiyuan Xu , Tsai-Ling Yang , Xiaoping Yang , Hao-Yu Yang , Junlin Yang , Haojin Yang , Guang Yang , Hongdou Yao , Xujiong Ye , Changchang Yin , Brett Young-Moxon , Jinhua Yu , Xiangyu Yue , Songtao Zhang , Angela Zhang , Kun Zhang , Xuejie Zhang , Lichi Zhang , Xiaoyue Zhang , Yazhuo Zhang , Lei Zhang , Jianguo Zhang , Xiang Zhang , Tianhao Zhang , Sicheng Zhao , Yu Zhao , Xiaomei Zhao , Liang Zhao , Yefeng Zheng , Liming Zhong , Chenhong Zhou , Xiaobing Zhou , Fan Zhou , Hongtu Zhu , Jin Zhu , Ying Zhuge , Weiwei Zong , Jayashree Kalpathy-Cramer , Keyvan Farahani , Christos Davatzikos , Koen van Leemput , Bjoern Menze

Breast cancer prediction models for mammography assume that annotations are available for individual images or regions of interest (ROIs), and that there is a fixed number of images per patient. These assumptions do not hold in real…

Computer Vision and Pattern Recognition · Computer Science 2024-10-22 Shreyasi Pathak , Jörg Schlötterer , Jeroen Geerdink , Jeroen Veltman , Maurice van Keulen , Nicola Strisciuglio , Christin Seifert