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

Pfob, André; Heil, Joerg

doi:10.1016/j.breast.2023.02.009

Cited by 4 publications

(3 citation statements)

References 39 publications

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“…De-escalation seeks to minimize the intensity of the treatment given to the patient, but it is vital to maintain equivalent rates of survival and ensure that the patient's long-term prognosis is not jeopardized. Long-term follow-up is necessary for patients receiving de-escalation techniques in order to track treatment effectiveness and identify any disease progression or recurrence [ 24 ].…”

Section: Reviewmentioning

confidence: 99%

Revolutionizing Breast Healthcare: Harnessing the Role of Artificial Intelligence

Singh,

Paruthy,

Belsariya

et al. 2023

Cureus

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Breast cancer has the highest incidence and second-highest mortality rate among all cancers. The management of breast cancer is being revolutionized by artificial intelligence (AI), which is improving early detection, pathological diagnosis, risk assessment, individualized treatment recommendations, and treatment response prediction. Nuclear medicine has used artificial intelligence (AI) for over 50 years, but more recent advances in machine learning (ML) and deep learning (DL) have given AI in nuclear medicine additional capabilities. AI accurately analyzes breast imaging scans for early detection, minimizing false negatives while offering radiologists reliable, swift image processing assistance. It smoothly fits into radiology workflows, which may result in early treatments and reduced expenditures. In pathological diagnosis, artificial intelligence improves the quality of diagnostic data by ensuring accurate diagnoses, lowering inter-observer variability, speeding up the review process, and identifying errors or poor slides. By taking into consideration nutritional, genetic, and environmental factors, providing individualized risk assessments, and recommending more regular tests for higher-risk patients, AI aids with the risk assessment of breast cancer. The integration of clinical and genetic data into individualized treatment recommendations by AI facilitates collaborative decision-making and resource allocation optimization while also enabling patient progress monitoring, drug interaction consideration, and alignment with clinical guidelines. AI is used to analyze patient data, imaging, genomic data, and pathology reports in order to forecast how a treatment would respond. These models anticipate treatment outcomes, make sure that clinical recommendations are followed, and learn from historical data. The implementation of AI in medicine is hampered by issues with data quality, integration with healthcare IT systems, data protection, bias reduction, and ethical considerations, necessitating transparency and constant surveillance. Protecting patient privacy, resolving biases, maintaining transparency, identifying fault for mistakes, and ensuring fair access are just a few examples of ethical considerations. To preserve patient trust and address the effect on the healthcare workforce, ethical frameworks must be developed. The amazing potential of AI in the treatment of breast cancer calls for careful examination of its ethical and practical implications. We aim to review the comprehensive role of artificial intelligence in breast cancer management.

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Section: Reviewmentioning

confidence: 99%

Revolutionizing Breast Healthcare: Harnessing the Role of Artificial Intelligence

Singh,

Paruthy,

Belsariya

et al. 2023

Cureus

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“…In many areas of medicine, digitalization plays a critical role and is beginning to impact nearly every part of the patient journey, from drug discovery and data collection to treatment and patient-reported outcomes [ 1 – 6 ]. Digital medicine includes a variety of fields, including digital health and care applications (DiGAs), telemedicine, mobile(m)Health solutions/wearable devices, artificial intelligence (AI)/data science, and structured data capture and management systems.…”

Section: Introductionmentioning

confidence: 99%

Status quo and future directions of digitalization in gynecology and obstetrics in Germany: a survey of the commission Digital Medicine of the German Society for Gynecology and Obstetrics

Pfob,

Hillen,

Seitz

et al. 2023

Arch Gynecol Obstet

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Purpose Digitalization plays a critical role and is beginning to impact every part of the patient journey, from drug discovery and data collection to treatment and patient-reported outcomes. We aimed to evaluate the status quo and future directions of digital medicine in the specialty of gynecology and obstetrics in Germany. Methods An anonymous questionnaire was distributed via the German Society of Gynecology and Obstetrics newsletter in December 2022. The questionnaire covered the domains baseline demographic information, telemedicine, digital health applications (DIGAs), and future expectations. Results In all, 91 participants completed the survey. Median age was 34 years; 67.4% (60 of 89) were female and 32.6% (29 of 89) were male. About 10% (9 of 88) have prescribed DIGAs to date and 14% (12 of 86) offer telemedical appointments. Among those who do not use digital medicine, very few plan to do so in the near future. Reasons include missing software interfaces, lack of time to try out new things, lack of knowledge, lack of monetary compensation (66.3%), and employee concerns. A majority agreed that digitalization will help to save time and improve patient care and that intelligent algorithms will aid clinicians in providing patient care to women. Conclusions The status quo and future directions of digital medicine in gynecology and obstetrics in Germany are characterized by contradicting expectations regarding the benefits of digital medicine and its actual implementation in clinical routine. This represents an important call to action to meet the requirements of modern patient care.

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“…For this Special Issue, we have invited outstanding, international experts to provide an overview of the current situation for both surgical and radiation treatments as well as to share their view on future perspectives, taking into account the potential adverse consequences of too hasty de-escalation [ [10] , [11] , [12] , [13] , [14] , [15] , [16] , [17] , [18] , [19] , [20] , [21] , [22] , [23] , [24] , [25] , [26] ]. “Time to find a balance” is, in fact, the subtitle of this monographic work; a document that aims to give the reader a broader/more in-depth vision of the potential implications of this ongoing process.…”

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confidence: 99%

De-escalation of loco-regional treatments: Time to find a balance

Gentilini,

Cardoso,

Senkus

et al. 2024

The Breast

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

Cited by 4 publications

References 39 publications

Revolutionizing Breast Healthcare: Harnessing the Role of Artificial Intelligence

Revolutionizing Breast Healthcare: Harnessing the Role of Artificial Intelligence

Status quo and future directions of digitalization in gynecology and obstetrics in Germany: a survey of the commission Digital Medicine of the German Society for Gynecology and Obstetrics

De-escalation of loco-regional treatments: Time to find a balance

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