Review
Biochemistry & Molecular Biology
Peng-Chan Lin, Yi-Shan Tsai, Yu-Min Yeh, Meng-Ru Shen
Summary: This article discusses the use of artificial intelligence in precision cancer medicine, covering topics such as computational prediction, mutational analysis, single-cell genomics, and text mining. By utilizing AI medical platforms and visualization techniques, large amounts of clinical biodata can be processed and understood quickly, leading to more accurate and rapid cancer therapy targets.
Article
Biochemistry & Molecular Biology
Norman E. Sharpless, Anthony R. Kerlavage
Summary: Artificial intelligence, machine learning, and deep learning have diverse applications in cancer research and clinical care, and the National Cancer Institute (NCI) is actively involved in supporting and advancing these technologies. In addition to developing and evaluating AI tools, NCI focuses on fostering a culture of data sharing, training the next generation of scientists, promoting interdisciplinary collaborations, and ensuring ethical principles in AI research and technologies.
BIOCHIMICA ET BIOPHYSICA ACTA-REVIEWS ON CANCER
(2021)
Article
Health Care Sciences & Services
Roman Zeleznik, Jakob Weiss, Jana Taron, Christian Guthier, Danielle S. Bitterman, Cindy Hancox, Benjamin H. Kann, Daniel W. Kim, Rinaa S. Punglia, Jeremy Bredfeldt, Borek Foldyna, Parastou Eslami, Michael T. Lu, Udo Hoffmann, Raymond Mak, Hugo J. W. L. Aerts
Summary: The study evaluated the use of a deep-learning system for heart segmentation on CT scans in radiation oncology treatment planning. The system, trained with multi-center data and validated in a real-world dataset, showed improved segmentation time and agreement compared to manual methods. The results indicate that deep-learning algorithms can be successfully applied across medical specialties to enhance clinical care.
NPJ DIGITAL MEDICINE
(2021)
Article
Oncology
Dipesh Uprety, Dongxiao Zhu, Howard (Jack) West
Summary: ChatGPT has the potential to be widely used in medical oncology to review patient records, interpret sequencing reports, and provide clinical trial options.
Article
Computer Science, Artificial Intelligence
Mauro Dragoni, Claudio Eccher, Antonella Ferro, Tania Bailoni, Rosa Maimone, Andrea Zorzi, Alessandro Bacchiega, Gabriele Stulzer, Chiara Ghidini
Summary: The onset of cancer is a traumatic experience that dramatically alters the lives of patients and their families, accompanied by physical, emotional, and psycho-social challenges. The COVID-19 pandemic has further complicated this scenario, significantly impacting the provision of optimal care for chronic patients. Telemedicine presents a solution by offering effective tools to monitor cancer patients' therapies, especially those administered at home.
ARTIFICIAL INTELLIGENCE IN MEDICINE
(2023)
Article
Medicine, General & Internal
M. Luke Marinovich, Elizabeth Wylie, William Lotter, Helen Lund, Andrew Waddell, Carolyn Madeley, Gavin Pereira, Nehmat Houssami
Summary: In this study, the accuracy of artificial intelligence (AI) was compared with radiologists in breast cancer screening. The AI algorithm showed a lower AUC compared to radiologists. However, AI detected interval cancers that were missed by radiologists.
Review
Computer Science, Information Systems
Yue Wang, Yaxin Song, Zhuo Ma, Xiaoxue Han
Summary: This article aims to study the fairness in medical AI from the perspectives of computer science, medical science, and social science. The results show that data is the foundation for fairness in medical AI, and legal, ethical, and technological measures all promote the implementation of fairness in medical AI. However, there are substantial discrepancies in the core aspects of fairness, such as the concept, influencing factors, and implementation measures, which require interdisciplinary discussions for practical implementation.
INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS
(2023)
Article
Computer Science, Artificial Intelligence
Fernando Martinez-Plumed, Pablo Barredo, Sean O. Heigeartaigh, Jose Hernandez-Orallo
Summary: Experimental benchmarks like ImageNet and Atari games are crucial for advancing AI research. An analysis of results and papers linked to 25 popular benchmarks reveals that competition and collaboration dynamics in AI research are still not well understood. The study provides an innovative methodology to explore the behavior of different entrants in challenges, from academia to tech giants, in response to achievements.
NATURE MACHINE INTELLIGENCE
(2021)
Article
Biology
Carlos Aguilar, Serena Pacile, Nicolas Weber, Pierre Fillard
Summary: We propose a methodology to monitor an AI tool for breast cancer screening in clinical centers. The AI is trained to detect suspicious regions in mammogram images and assign them a suspicion score. The behavior of the AI was assessed by comparing its score distribution in different centers to a reference distribution, and the results show that the AI behaved as expected. This methodology can help improve software monitoring in hospitals.
Editorial Material
Biochemistry & Molecular Biology
Zachi I. Attia, Paul A. Friedman
Summary: By applying artificial intelligence to electrocardiograms recorded by patients using Apple watches, we conducted a prospective, digital, remote study to enable large-scale screening for left ventricular dysfunction, a serious and under-detected cardiac disease. The study found that patients engaged with the system and that the watch electrocardiograms effectively screened for the disease.
Article
Radiology, Nuclear Medicine & Medical Imaging
V. Romeo, P. Clauser, S. Rasul, P. Kapetas, P. Gibbs, P. A. T. Baltzer, M. Hacker, R. Woitek, T. H. Helbich, K. Pinker
Summary: The study aimed to evaluate whether a radiomics and machine learning model utilizing quantitative parameters and radiomics features extracted from simultaneous multiparametric F-18-FDG PET/MRI images can effectively distinguish between benign and malignant breast lesions.
EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
(2022)
Article
Computer Science, Artificial Intelligence
Kerstin N. Vokinger, Urs Gasser
Summary: Regulatory frameworks for artificial intelligence are being developed on both sides of the Atlantic, eagerly anticipated by the scientific and industrial community. Commonalities and differences in approaches to AI in medicine are beginning to emerge.
NATURE MACHINE INTELLIGENCE
(2021)
Letter
Engineering, Biomedical
Aaron Lawson McLean
Summary: This critique examines the integration of AI technology, particularly OpenAI's GPT-4 and its interface, ChatGPT, in spinal surgery. It explores potential algorithmic bias, unique challenges in surgical domains, access and equity issues, cost implications, global disparities in technology adoption, and the concept of technological determinism. The critique highlights the impact of biases on healthcare outcomes, challenges in surgical decision-making, concerns over access and equity, global collaboration, and the importance of human judgement in healthcare. It calls for a comprehensive evaluation of AI integration to ensure equitable and quality care.
ANNALS OF BIOMEDICAL ENGINEERING
(2023)
Review
Medicine, General & Internal
Filippo Pesapane, Paolo De Marco, Anna Rapino, Eleonora Lombardo, Luca Nicosia, Priyan Tantrige, Anna Rotili, Anna Carla Bozzini, Silvia Penco, Valeria Dominelli, Chiara Trentin, Federica Ferrari, Mariagiorgia Farina, Lorenza Meneghetti, Antuono Latronico, Francesca Abbate, Daniela Origgi, Gianpaolo Carrafiello, Enrico Cassano
Summary: Artificial intelligence has potential in addressing various medical challenges in breast cancer care. Radiomics, a quantitative approach to medical imaging using artificial intelligence, can enhance clinical decision making by providing more data. This review focuses on the evolution of AI in breast imaging, with a particular emphasis on handcrafted and deep learning radiomics. The methodology and implementation of radiomics in breast cancer are summarized based on recent scientific literature, with discussions on limitations and challenges of integration into clinical practice.
JOURNAL OF CLINICAL MEDICINE
(2023)
Article
Mathematical & Computational Biology
Rachel St. Clair, L. Andrew Coward, Susan Schneider
Summary: The study introduces a novel learning model, the Recommendation Architecture (RA) Model, which combines consequence feedback and non-consequence feedback. Results show that the RA model learns novelty more efficiently and can accurately return to prior learning with less computational resources expenditure, making it more similar to human learning in terms of resource efficiency.
FRONTIERS IN COMPUTATIONAL NEUROSCIENCE
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Tong Li, Darren Lockie, Michelle Clemson, Nehmat Houssami
Summary: This study compared the secondary outcomes of digital breast tomosynthesis (DBT) and digital mammography (DM) screening. The results showed that DBT detected more benign and malignant lesions compared to DM, and generally required more procedures.
JOURNAL OF MEDICAL IMAGING AND RADIATION ONCOLOGY
(2023)
Article
Computer Science, Information Systems
Yves Saint James Aquino, Wendy A. Rogers, Annette Braunack-Mayer, Helen Frazer, Khin Than Win, Nehmat Houssami, Christopher Degeling, Christopher Semsarian, Stacy M. Carter
Summary: This study examines the issue of deskilling due to healthcare artificial intelligence (AI) from the perspective of professional stakeholders involved in the development and regulation of AI. The findings reveal diverse views on the extent of AI-enabled automation in healthcare work, the impact of AI on clinical skills, and the different models of healthcare work. The study highlights the importance of considering the perspectives of various stakeholders in decision-making regarding AI development and deployment in healthcare.
INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS
(2023)
Letter
Public, Environmental & Occupational Health
Brooke Nickel, Hankiz Dolan, Nehmat Houssami, Erin Cvejic, Meagan Brennan, Jolyn Hersch, Melanie Dorrington, Angela Verde, Lisa Vaccaro, Kirsten McCaffery
Summary: This study examined factors associated with women's intentions for supplemental screening after receiving notification of dense breasts. The results showed that women with higher levels of breast cancer worry, private health insurance, a family history of breast cancer, and previous mammography screenings were more likely to have intentions for supplemental screening. Understanding these factors is important for health systems considering widespread notification of dense breasts and discussing the benefits and harms of supplemental screening.
JOURNAL OF MEDICAL SCREENING
(2023)
Article
Environmental Sciences
Tanvi Pandya, Zixuan Liu, Hankiz Dolan, Jolyn Hersch, Meagan Brennan, Nehmat Houssami, Brooke Nickel
Summary: This study examined women's responses and intentions if notified that they had dense breasts. The results showed that half of the women would feel a little anxious, while 29.5% would not feel anxious. The most common responses were to consult their doctor for information/advice and considering supplemental screening.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2023)
Editorial Material
Oncology
Alberto Stefano Tagliafico, Nehmat Houssami
Article
Oncology
E. -A. Bonci, J. Correia Anacleto, M. -J. Cardoso
Summary: Simple breast conservation surgery (sBCS) has advanced to oncoplastic breast procedures (OBP) to improve psychosocial well-being and cosmetic outcome. Despite the increase in OBP use, the choice between sBCS and OBP is difficult. Research on their safety, efficacy, and patient-reported outcomes is lacking.
Article
Ethics
Yves Saint James Aquino, Stacy M. Carter, Nehmat Houssami, Annette Braunack-Mayer, Khin Than Win, Chris Degeling, Lei Wang, Wendy A. Rogers
Summary: This study examines strategies to mitigate algorithmic bias in healthcare AI and investigates the question of responsibility for bias. The findings reveal divergent views on bias as a problem, strategies to mitigate bias, and whether to include sociocultural identifiers in AI development. The study suggests interdisciplinary collaboration, tailored engagement activities, empirical studies, participatory methods, and increased diversity and inclusion as potential responses.
JOURNAL OF MEDICAL ETHICS
(2023)
Review
Sport Sciences
Ines Ramos Correia, Vasco Cardoso, Catarina Cargaleiro, Joao P. Magalhaes, Megan Hetherington-Rauth, Gil B. Rosa, Carla Malveiro, Leonor Vasconcelos de Matos, Maria Joao Cardoso, Luis B. Sardinha
Summary: This systematic review and meta-analysis aimed to investigate the effects of home-based exercise on physical fitness in cancer patients undergoing active treatment. The results showed that regular home-based exercise programs are effective in improving the 6-minute walk test for cancer patients undergoing active treatment, but no significant effects were found for muscle strength and body composition.
JOURNAL OF SCIENCE AND MEDICINE IN SPORT
(2023)
Review
Sport Sciences
Carla Malveiro, Ines R. Correia, Catarina Cargaleiro, Joao P. Magalhaes, Leonor Vasconcelos de Matos, Sofia Hilario, Luis B. Sardinha, Maria Joao Cardoso
Summary: This systematic review analyzed the effects of different exercise protocols on physical fitness, quality of life, cancer-related fatigue, and sleep quality in patients with different types of cancer undergoing neoadjuvant treatment. The review found that exercise interventions appeared to improve cardiorespiratory fitness, muscle strength, body composition, and overall quality of life.
JOURNAL OF SCIENCE AND MEDICINE IN SPORT
(2023)
Article
Engineering, Biomedical
Rafaela Timoteo, David Pinto, Marta Martinho, Pedro Gouveia, Daniel Simoes Lopes, Carlos Mavioso, Maria Joao Cardoso
Summary: Augmented reality (AR) can be beneficial for deep inferior epigastric artery perforator (DIEAP) flap reconstruction surgeries in terms of surgery planning and outcomes improvement. However, the anchorage of three-dimensional (3D) models to the patient's body during surgery does not consider skin deformation, leading to mismatch between the models and the patient. This study compares the 3D deformation registration from computed tomography angiography (CTA) position to surgical position and estimates the patient's skin deformation. The results show that there are cases of significant deformation, indicating the need for accurate 3D models using CTA data and considering projection errors when using AR technology.
MEDICAL ENGINEERING & PHYSICS
(2023)
Article
Multidisciplinary Sciences
Orit Kaidar-Person, Marilia Antunes, Jaime D. Cardoso, Oriana Ciani, Helena Cruz, Rosa Di Micco, Oreste Gentilini, Tiago Goncalves, Pedro Gouveia, Jorg Heil, Pawel Kabata, Daniela Lopes, Marta Martinho, Henrique P. Martins, Carlos Mavioso, Martin Mika, Helena Montenegro, Helder Oliveira, Andre Pfob, Nicole Rotmensz, Timo Schinkothe, Giovani Silva, Rosana Tarricone, Maria-Joao Cardoso, CINDERELLA Consortium
Summary: The CINDERELLA trial aims to evaluate the impact of an artificial-intelligence cloud-based platform on patient education prior to therapy for breast cancer. The platform will provide patients with a visual representation of their potential aesthetic outcomes and an objective evaluation. The goal is to improve patient satisfaction, enhance psychosocial well-being, and reduce the need for additional surgeries.
Review
Medicine, General & Internal
Orit Kaidar-Person, Andre Pfob, Oreste Davide Gentilini, Bettina Borisch, Ana Bosch, Maria Joao Cardoso, Giuseppe Curigliano, Jana De Boniface, Carsten Denkert, Nik Hauser, Joerg Heil, Michael Knauer, Thorsten Kuehn, Han-Byoel Lee, Sibylle Loibl, Meinrad Mannhart, Icro Meattini, Giacomo Montagna, Katja Pinker, Fiorita Poulakaki, Isabel T. Rubio, Patrizia Sager, Petra Steyerova, Christoph Tausch, Trine Tramm, Marie-Jeanne Vrancken Peeters, Lynda Wyld, Jong Han Yu, Walter Paul Weber, Philip Poortmans, Peter Dubsky
Summary: Clinical axillary lymph node management in early breast cancer has evolved to involve the entire multidisciplinary team. The Lucerne Toolbox, a multidisciplinary consortium, addresses the challenges in clinical axillary lymph node management, proposing targeted imaging and standardized pathology as prerequisites to planning therapy, and the replacement of axillary lymph node dissection with sentinel lymph node biopsy in most scenarios. Positive patient outcomes should be driven by both low recurrence risks and low rates of lymphoedema.
Article
Oncology
Pedro F. Gouveia, Rogelio Luna, Francisco Fontes, David Pinto, Carlos Mavioso, Joao Anacleto, Rafaela Timoteo, Joao Santinha, Tiago Marques, Fatima Cardoso, Maria Joao Cardoso
Summary: Augmented reality (AR) has the potential to benefit the healthcare sector through real-time data acquisition, machine learning-aided processing, and visualization. This paper focuses on the future use of AR in breast surgery education, specifically surgical telementoring and impalpable breast cancer localization. The success of these applications depends on improvements in data transformation and infrastructures. (c) 2023 S. Karger AG, Basel
Article
Radiology, Nuclear Medicine & Medical Imaging
Andrea Cozzi, Giovanni Di Leo, Nehmat Houssami, Fiona J. Gilbert, Thomas H. Helbich, Marina Alvarez Benito, Corinne Balleyguier, Massimo Bazzocchi, Peter Bult, Massimo Calabrese, Julia Camps Herrero, Francesco Cartia, Enrico Cassano, Paola Clauser, Marcos de Lima F. Docema, Catherine Depretto, Valeria Dominelli, Gabor Forrai, Rossano Girometti, Steven E. Harms, Sarah Hilborne, Raffaele Ienzi, Marc B. I. Lobbes, Claudio Losio, Ritse M. Mann, Stefania Montemezzi, Inge-Marie Obdeijn, Umit A. Ozcan, Federica Pediconi, Katja Pinker, Heike Preibsch, Jose L. Raya Povedano, Carolina Rossi Saccarelli, Daniela Sacchetto, Gianfranco P. Scaperrotta, Margrethe Schlooz, Botond K. Szabo, Donna B. Taylor, Ozden S. Ulus, Mireille Van Goethem, Jeroen Veltman, Stefanie Weigel, Evelyn Wenkel, Chiara Zuiani, Francesco Sardanelli
Summary: This study aimed to investigate the mastectomy and reoperation rates in breast cancer patients who underwent MRI for screening or diagnostic purposes. The results showed that patients who had MRI for screening had higher mastectomy rates and lower reoperation rates compared to those who had MRI for diagnostic purposes.
EUROPEAN RADIOLOGY
(2023)
Article
Oncology
Pedro Filipe Pereira Gouveia, Rogelio Luna, Francisco Fontes, David Pinto, Carlos Mavioso, Joao Anacleto, Rafaela Timoteo, Joao Santinha, Tiago Marques, Fatima Cardoso, Maria Joao Cardoso
Summary: Augmented Reality (AR) has the potential to bring numerous benefits and educational applications in the virtual health ecosystem. This paper focuses on the future applications of AR in breast surgery education, specifically discussing two potential use cases and the technical requirements to make them possible.
