Advances in sensor technologies for breast cancer detection: a comprehensive review of imaging and non-imaging approaches
Abstract Early detection of breast cancer, a deadly disease affecting millions of women worldwide, is crucial for better survival rates while minimizing the complexity of treatment procedures. Advances in sensor technologies have revolutionized breast cancer detection, providing non-invasive, accura...
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| Format: | Article |
| Language: | English |
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Springer
2025-07-01
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| Series: | Discover Artificial Intelligence |
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| Online Access: | https://doi.org/10.1007/s44163-025-00443-1 |
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| author | Emmy Bhatti Prabhpreet Kaur |
| author_facet | Emmy Bhatti Prabhpreet Kaur |
| author_sort | Emmy Bhatti |
| collection | DOAJ |
| description | Abstract Early detection of breast cancer, a deadly disease affecting millions of women worldwide, is crucial for better survival rates while minimizing the complexity of treatment procedures. Advances in sensor technologies have revolutionized breast cancer detection, providing non-invasive, accurate, and cost-effective diagnostic solutions. This paper reviews state-of-the-art sensors currently used in breast cancer detection systems, including imaging and non-imaging technologies such as optical, thermal, electromagnetic, ultrasound, and biosensors. Modalities imaging-based types include mammography, ultrasound, and MRI, which are still the gold standard for detection because of their good sensitivity. Other technologies that are not imaging-based include microwave, radiofrequency, and electrical impedance tomography, which are more promising in resource-deprived settings. Molecular-level detection with a defined biomarker is feasible using nanotechnology and biosensing. Wearable sensors and artificial intelligence-based systems are essential for continuous monitoring and data interpretation. Major improvements have been realized in the performance of sensors, which have been measured by parameters such as specificity, sensitivity, and reliability. Nanotechnology and multi-sensor capability have enhanced early detection and patient monitoring. However, challenges persist, including accessibility, monetary barriers, and standardization in clinical applications. This research highlights the potential of a multi-sensor system, driven by real-time monitoring and powered by machine learning algorithms, to address the gaps in breast cancer diagnosis. Such advancements would benefit dispersed and equitable healthcare solutions, addressing limitations of the current state and paving the way for full-fledged implementation in clinical environments. |
| format | Article |
| id | doaj-art-81a1001795bb48fab35e2d47f3dc09ea |
| institution | Kabale University |
| issn | 2731-0809 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Springer |
| record_format | Article |
| series | Discover Artificial Intelligence |
| spelling | doaj-art-81a1001795bb48fab35e2d47f3dc09ea2025-08-20T03:46:21ZengSpringerDiscover Artificial Intelligence2731-08092025-07-015111610.1007/s44163-025-00443-1Advances in sensor technologies for breast cancer detection: a comprehensive review of imaging and non-imaging approachesEmmy Bhatti0Prabhpreet Kaur1Department of Computer Engineering and Technology, Guru Nanak Dev UniversityDepartment of Computer Engineering and Technology, Guru Nanak Dev UniversityAbstract Early detection of breast cancer, a deadly disease affecting millions of women worldwide, is crucial for better survival rates while minimizing the complexity of treatment procedures. Advances in sensor technologies have revolutionized breast cancer detection, providing non-invasive, accurate, and cost-effective diagnostic solutions. This paper reviews state-of-the-art sensors currently used in breast cancer detection systems, including imaging and non-imaging technologies such as optical, thermal, electromagnetic, ultrasound, and biosensors. Modalities imaging-based types include mammography, ultrasound, and MRI, which are still the gold standard for detection because of their good sensitivity. Other technologies that are not imaging-based include microwave, radiofrequency, and electrical impedance tomography, which are more promising in resource-deprived settings. Molecular-level detection with a defined biomarker is feasible using nanotechnology and biosensing. Wearable sensors and artificial intelligence-based systems are essential for continuous monitoring and data interpretation. Major improvements have been realized in the performance of sensors, which have been measured by parameters such as specificity, sensitivity, and reliability. Nanotechnology and multi-sensor capability have enhanced early detection and patient monitoring. However, challenges persist, including accessibility, monetary barriers, and standardization in clinical applications. This research highlights the potential of a multi-sensor system, driven by real-time monitoring and powered by machine learning algorithms, to address the gaps in breast cancer diagnosis. Such advancements would benefit dispersed and equitable healthcare solutions, addressing limitations of the current state and paving the way for full-fledged implementation in clinical environments.https://doi.org/10.1007/s44163-025-00443-1Breast cancer detectionSensor technologiesImaging sensorsBiosensorsNanotechnologyMachine learning |
| spellingShingle | Emmy Bhatti Prabhpreet Kaur Advances in sensor technologies for breast cancer detection: a comprehensive review of imaging and non-imaging approaches Discover Artificial Intelligence Breast cancer detection Sensor technologies Imaging sensors Biosensors Nanotechnology Machine learning |
| title | Advances in sensor technologies for breast cancer detection: a comprehensive review of imaging and non-imaging approaches |
| title_full | Advances in sensor technologies for breast cancer detection: a comprehensive review of imaging and non-imaging approaches |
| title_fullStr | Advances in sensor technologies for breast cancer detection: a comprehensive review of imaging and non-imaging approaches |
| title_full_unstemmed | Advances in sensor technologies for breast cancer detection: a comprehensive review of imaging and non-imaging approaches |
| title_short | Advances in sensor technologies for breast cancer detection: a comprehensive review of imaging and non-imaging approaches |
| title_sort | advances in sensor technologies for breast cancer detection a comprehensive review of imaging and non imaging approaches |
| topic | Breast cancer detection Sensor technologies Imaging sensors Biosensors Nanotechnology Machine learning |
| url | https://doi.org/10.1007/s44163-025-00443-1 |
| work_keys_str_mv | AT emmybhatti advancesinsensortechnologiesforbreastcancerdetectionacomprehensivereviewofimagingandnonimagingapproaches AT prabhpreetkaur advancesinsensortechnologiesforbreastcancerdetectionacomprehensivereviewofimagingandnonimagingapproaches |