Artificial Intelligence in Medical Sensors for Clinical Decisions

Dermatologist-level classification of skin cancer with deep neural networks

Esteva, A., Kuprel, B., Novoa, R. A., Ko, J., Swetter, S. M., Blau, H. M., & Thrun, S. (2017) · Nature · doi:10.1038/nature21056 · Cited by 14,362 · see citing works

Communication-Efficient Learning of Deep Networks from Decentralized Data

McMahan, H. B., Moore, E., Ramage, D., Hampson, S., & Arcas, B. A. Y. (2016) · arXiv · doi:10.48550/arxiv.1602.05629 · Cited by 14,215 · see citing works

Practical Secure Aggregation for Privacy-Preserving Machine Learning

Bonawitz, K., Ivanov, V., Kreuter, B., Marcedone, A., McMahan, H. B., Patel, S., Ramage, D., Segal, A., & Seth, K. (2017) · Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security · doi:10.1145/3133956.3133982 · Cited by 3,956 · see citing works

Wearable biosensors for healthcare monitoring

Kim, J., Campbell, A. S., de Ávila, B. E.-F., & Wang, J. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0045-y · Cited by 3,373 · see citing works

Understanding Machine Learning: From Theory to Algorithms

Shalev-Shwartz, S., & Ben-David, S. (2014) · doi:10.1017/cbo9781107298019 · Cited by 3,115 · see citing works

The practical implementation of artificial intelligence technologies in medicine

He, J., Baxter, S. L., Xu, J., Xu, J., Zhou, X., & Zhang, K. (2019) · Nature Medicine · doi:10.1038/s41591-018-0307-0 · Cited by 2,246 · see citing works

End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography

Ardila, D., Kiraly, A. P., Bharadwaj, S., Choi, B., Reicher, J. J., Peng, L., Tse, D., Etemadi, M., Ye, W., Corrado, G., et al. (2019) · Nature Medicine · doi:10.1038/s41591-019-0447-x · Cited by 2,167 · see citing works

A graphene-based electrochemical device with thermoresponsive microneedles for diabetes monitoring and therapy

Lee, H., Choi, T. K., Lee, Y. B., Cho, H. R., Ghaffari, R., Wang, L., Choi, H. J., Chung, T. D., Lu, N., Hyeon, T., et al. (2016) · Nature Nanotechnology · doi:10.1038/nnano.2016.38 · Cited by 1,802 · see citing works

Learning Differentially Private Recurrent Language Models

McMahan, H. B., Ramage, D., Talwar, K., & Zhang, L. (2017) · arXiv · doi:10.48550/arxiv.1710.06963 · Cited by 849 · see citing works

Advancing Biosensors with Machine Learning

Cui, F., Yue, Y., Zhang, Y., Zhang, Z., & Zhou, H. S. (2020) · ACS Sensors · doi:10.1021/acssensors.0c01424 · Cited by 786 · see citing works

Electrochemical Immunosensors for Detection of Cancer Protein Biomarkers

Chikkaveeraiah, B. V., Bhirde, A. A., Morgan, N. Y., Eden, H. S., & Chen, X. S. (2012) · ACS Nano · doi:10.1021/nn3023969 · Cited by 721 · see citing works

Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges

Usama, M., Qadir, J., Raza, A., Arif, H., Yau, K. A., Elkhatib, Y., Hussain, A., & Al‐Fuqaha, A. (2019) · IEEE Access · doi:10.1109/access.2019.2916648 · Cited by 621 · see citing works

Remote Monitoring of Human Vital Signs Using mm-Wave FMCW Radar

Alizadeh, M., Shaker, G. S. A., Almeida, J. C., Morita, P. P., & Safavi-Naeini, S. (2019) · IEEE Access · doi:10.1109/access.2019.2912956 · Cited by 540 · see citing works

Diagnosis and Classification of 17 Diseases from 1404 Subjects via Pattern Analysis of Exhaled Molecules

Nakhleh, M. K., Amal, H., Jeries, R., Broza, Y. Y., Aboud, M., Gharra, A., Ivgi, H., Khatib, S., Badarneh, S., Har‐Shai, L., et al. (2016) · ACS Nano · doi:10.1021/acsnano.6b04930 · Cited by 510 · see citing works

Flexible Hybrid Sensors for Health Monitoring: Materials and Mechanisms to Render Wearability

Gao, Y., Yu, L., Yeo, J. C., & Lim, C. T. (2019) · Advanced Materials · doi:10.1002/adma.201902133 · Cited by 508 · see citing works

Early-Stage Lung Cancer Diagnosis by Deep Learning-Based Spectroscopic Analysis of Circulating Exosomes

Shin, H., Oh, S., Hong, S., Kang, M.-S., Kang, D., Ji, Y.-G., Choi, B. H., Kang, K., Jeong, H., Park, Y., et al. (2020) · ACS Nano · doi:10.1021/acsnano.9b09119 · Cited by 508 · see citing works

Integrating Artificial Intelligence and Nanotechnology for Precision Cancer Medicine

Adir, O., Poley, M., Chen, G., Froim, S., Krinsky, N., Shklover, J., Shainsky‐Roitman, J., Lammers, T., & Schroeder, A. (2020) · Advanced Materials · doi:10.1002/adma.201901989 · Cited by 496 · see citing works

Disease Detection with Molecular Biomarkers: From Chemistry of Body Fluids to Nature-Inspired Chemical Sensors

Broza, Y. Y., Zhou, X., Yuan, M., Qu, D., Zheng, Y., Vishinkin, R., Khatib, M., Wu, W., & Haick, H. (2019) · Chemical Reviews · doi:10.1021/acs.chemrev.9b00437 · Cited by 461 · see citing works

Advanced Materials for Use in Soft Self‐Healing Devices

Huynh, T., Sonar, P. M., & Haick, H. (2017) · Advanced Materials · doi:10.1002/adma.201604973 · Cited by 445 · see citing works

Smartphone Sensors for Health Monitoring and Diagnosis

Majumder, S., & Deen, M. J. (2019) · Sensors · doi:10.3390/s19092164 · Cited by 440 · see citing works

Saliva as a diagnostic tool for oral and systemic diseases

Javaid, M. A., Ahmed, A. S., Durand, R., & Tran, S. D. (2016) · Journal of Oral Biology and Craniofacial Research · doi:10.1016/j.jobcr.2015.08.006 · Cited by 431 · see citing works

Artificial intelligence biosensors: Challenges and prospects

Jin, X., Liu, C., Xu, T., Su, L., & Zhang, X. (2020) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2020.112412 · Cited by 399 · see citing works

Wearable Sensors for Biochemical Sweat Analysis

Bandodkar, A. J., Jeang, W. J., Ghaffari, R., & Rogers, J. A. (2019) · Annual Review of Analytical Chemistry · doi:10.1146/annurev-anchem-061318-114910 · Cited by 387 · see citing works

Multiplexed Nanomaterial-Based Sensor Array for Detection of COVID-19 in Exhaled Breath

Shan, B., Broza, Y. Y., Li, W., Wang, Y., Wu, S., Liu, Z., Wang, J., Gui, S., Wang, L., Zhang, Z., et al. (2020) · ACS Nano · doi:10.1021/acsnano.0c05657 · Cited by 384 · see citing works

Electronic Noses: From Advanced Materials to Sensors Aided with Data Processing

Hu, W., Wan, L., Jian, Y., Ren, C., Jin, K., Su, X., Bai, X., Haick, H., Yao, M., & Wu, W. (2018) · Advanced Materials Technologies · doi:10.1002/admt.201800488 · Cited by 368 · see citing works

Nanomaterial-Based Sensors for Detection of Disease by Volatile Organic Compounds

Broza, Y. Y., & Haick, H. (2013) · Nanomedicine · doi:10.2217/nnm.13.64 · Cited by 360 · see citing works

The Era of Digital Health: A Review of Portable and Wearable Affinity Biosensors

Tu, J., Torrente-Rodríguez, R. M., Wang, M., & Gao, W. F. (2019) · Advanced Functional Materials · doi:10.1002/adfm.201906713 · Cited by 359 · see citing works

Vital-sign monitoring and spatial tracking of multiple people using a contactless radar-based sensor

Mercuri, M., Lorato, I. R., Liu, Y., Wieringa, F. P., Hoof, C. A. V., & Torfs, T. (2019) · Nature Electronics · doi:10.1038/s41928-019-0258-6 · Cited by 357 · see citing works

Self‐Healable Multifunctional Electronic Tattoos Based on Silk and Graphene

Wang, Q., Ling, S., Liang, X., Wang, H., Lü, H., & Zhang, Y. (2019) · Advanced Functional Materials · doi:10.1002/adfm.201808695 · Cited by 348 · see citing works

Dynamic-Fusion-Based Federated Learning for COVID-19 Detection

Zhang, W., Zhou, T., Lu, Q., Wang, X., Zhu, C., Sun, H., Wang, Z., Lo, S. K., & Wang, F.-Y. (2021) · IEEE Internet of Things Journal · doi:10.1109/jiot.2021.3056185 · Cited by 329 · see citing works

Advanced Materials for Health Monitoring with Skin‐Based Wearable Devices

Jin, H., Abu‐Raya, Y. S., & Haick, H. (2017) · Advanced Healthcare Materials · doi:10.1002/adhm.201700024 · Cited by 317 · see citing works

Prospects and Challenges of Volatile Organic Compound Sensors in Human Healthcare

Jalal, A. H., Alam, F., Roychoudhury, S., Umasankar, Y., Pala, N., & Bhansali, S. (2018) · ACS Sensors · doi:10.1021/acssensors.8b00400 · Cited by 315 · see citing works

FedVision: An Online Visual Object Detection Platform Powered by Federated Learning

Liu, Y., Huang, A., Luo, Y., Huang, H., Liu, Y., Chen, Y., Feng, L., Chen, T., Yu, H., & Yang, Q. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v34i08.7021 · Cited by 310 · see citing works

DataSHIELD: taking the analysis to the data, not the data to the analysis

Gaye, A., Marcon, Y., Isaeva, J., Laflamme, P., Turner, A. J., Jones, E. M., Minion, J. T., Boyd, A. W., Newby, C., Nuotio, M.-L., et al. (2014) · International Journal of Epidemiology · doi:10.1093/ije/dyu188 · Cited by 307 · see citing works

Hybrid Volatolomics and Disease Detection

Broza, Y. Y., Mochalski, P., Ruzsányi, V., Amann, A., & Haick, H. (2015) · Angewandte Chemie International Edition · doi:10.1002/anie.201500153 · Cited by 291 · see citing works

Medical Imaging of Microrobots: Toward In Vivo Applications

Aziz, A., Pane, S., Iacovacci, V., Koukourakis, N., Czarske, J. W., Menciassi, A., Medina‐Sánchez, M., & Schmidt, O. G. (2020) · ACS Nano · doi:10.1021/acsnano.0c05530 · Cited by 290 · see citing works

Synergy between nanomaterials and volatile organic compounds for non-invasive medical evaluation

Broza, Y. Y., Vishinkin, R., Barash, O., Nakhleh, M. K., & Haick, H. (2018) · Chemical Society Reviews · doi:10.1039/c8cs00317c · Cited by 275 · see citing works

Autonomous Flexible Sensors for Health Monitoring

Huynh, T., & Haick, H. (2018) · Advanced Materials · doi:10.1002/adma.201802337 · Cited by 260 · see citing works

Ultrasensitive silicon nanowire for real-world gas sensing: Noninvasive diagnosis of cancer from breath volatolome

Shehada, N., Brönstrup, G., Funka, K., Christiansen, S., Leja, M., & Haick, H. (2015) · Nano Letters · doi:10.1021/nl504482t · Cited by 255 · see citing works

A call for deep-learning healthcare

Norgeot, B., Glicksberg, B. S., & Butte, A. J. (2018) · Nature Medicine · doi:10.1038/s41591-018-0320-3 · Cited by 252 · see citing works

Insulin dose optimization using an automated artificial intelligence-based decision support system in youths with type 1 diabetes

Nimri, R., Battelino, T., Laffel, L. M., Slover, R. H., Schatz, D., Weinzimer, S. A., Dovc, K., Danne, T., Phillip, M., NextDREAM Consortium, et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-1045-7 · Cited by 242 · see citing works

Artificial sensing intelligence with silicon nanowires for ultraselective detection in the gas phase

Wang, B., Cancilla, J. C., Torrecilla, J. S., & Haick, H. (2014) · Nano Letters · doi:10.1021/nl404335p · Cited by 236 · see citing works

Wearable and Implantable Electronics: Moving toward Precision Therapy

Song, Y., Min, J., & Gao, W. F. (2019) · ACS Nano · doi:10.1021/acsnano.9b08323 · Cited by 232 · see citing works

Machine Learning in Nanoscience: Big Data at Small Scales

Brown, K. A., Brittman, S., Maccaferri, N., Jariwala, D., & Celano, U. (2020) · Nano Letters · doi:10.1021/acs.nanolett.9b04090 · Cited by 229 · see citing works

Silicon Nanowire Sensors Enable Diagnosis of Patients <i>via</i> Exhaled Breath

Shehada, N., Cancilla, J. C., Torrecilla, J. S., Pariente, E. S., Brönstrup, G., Christiansen, S., Johnson, D. W., Leja, M., Davies, M. P. A., Liran, O., et al. (2016) · ACS Nano · doi:10.1021/acsnano.6b03127 · Cited by 227 · see citing works

Frailty and healthcare costs—longitudinal results of a prospective cohort study

Hajek, A., Bock, J., Saum, K.-U., Matschinger, H., Brenner, H., Holleczek, B., Haefeli, W. E., Heider, D., & König, H. (2017) · Age and Ageing · doi:10.1093/ageing/afx157 · Cited by 217 · see citing works

Self‐Healing, Fully Functional, and Multiparametric Flexible Sensing Platform

Huynh, T., & Haick, H. (2015) · Advanced Materials · doi:10.1002/adma.201504104 · Cited by 210 · see citing works

Materials and Wearable Devices for Autonomous Monitoring of Physiological Markers

Wu, W., & Haick, H. (2018) · Advanced Materials · doi:10.1002/adma.201705024 · Cited by 208 · see citing works

Epidermal Patch with Glucose Biosensor: pH and Temperature Correction toward More Accurate Sweat Analysis during Sport Practice

Wiorek, A., Parrilla, M., Cuartero, M., & Crespo, G. A. (2020) · Analytical Chemistry · doi:10.1021/acs.analchem.0c02211 · Cited by 201 · see citing works

Nanoscale Sensor Technologies for Disease Detection via Volatolomics

Vishinkin, R., & Haick, H. (2015) · Small · doi:10.1002/smll.201501904 · Cited by 198 · see citing works

The regulation of mobile health applications

Barton, A. (2012) · BMC Medicine · doi:10.1186/1741-7015-10-46 · Cited by 182 · see citing works

Nanomaterials for cross-reactive sensor arrays

Tisch, U., & Haick, H. (2010) · MRS Bulletin · doi:10.1557/mrs2010.509 · Cited by 172 · see citing works

Self-Healable Sensors Based Nanoparticles for Detecting Physiological Markers via Skin and Breath: Toward Disease Prevention via Wearable Devices

Jin, H., Huynh, T.-P., & Haick, H. (2016) · Nano Letters · doi:10.1021/acs.nanolett.6b01066 · Cited by 167 · see citing works

A Multifunctional Electronic Skin Empowered with Damage Mapping and Autonomic Acceleration of Self‐Healing in Designated Locations

Khatib, M., Zohar, O., Saliba, W., & Haick, H. (2020) · Advanced Materials · doi:10.1002/adma.202000246 · Cited by 164 · see citing works

Cancer metabolomic markers in urine: evidence, techniques and recommendations

Dinges, S. S., Hohm, A., Vandergrift, L. A., Nowak, J., Habbel, P., Kaltashov, I. A., & Cheng, L. L. (2019) · Nature Reviews Urology · doi:10.1038/s41585-019-0185-3 · Cited by 161 · see citing works

Flexible Self‐Repairing Materials for Wearable Sensing Applications: Elastomers and Hydrogels

Li, S., Zhou, X., Dong, Y., & Li, J. (2020) · Macromolecular Rapid Communications · doi:10.1002/marc.202000444 · Cited by 149 · see citing works

Printing Flexible and Hybrid Electronics for Human Skin and Eye‐Interfaced Health Monitoring Systems

Kim, K., Kim, B., & Lee, C. H. (2019) · Advanced Materials · doi:10.1002/adma.201902051 · Cited by 146 · see citing works

Wearable motion sensors to continuously measure real-world physical activities

Dobkin, B. H. (2013) · Current Opinion in Neurology · doi:10.1097/wco.0000000000000026 · Cited by 142 · see citing works

A Fully Integrated Wireless Flexible Ammonia Sensor Fabricated by Soft Nano-Lithography

Tang, N., Zhou, C. J., Xu, L., Jiang, Y., Qu, H., & Duan, X. (2019) · ACS Sensors · doi:10.1021/acssensors.8b01690 · Cited by 136 · see citing works

Applying Internet of Things and Machine-Learning for Personalized Healthcare: Issues and Challenges

Ahamed, F., & Farid, F. (2018) · International Conference on Machine Learning and Data Engineering (iCMLDE) · doi:10.1109/icmlde.2018.00014 · Cited by 130 · see citing works

Noninvasive Precision Screening of Prostate Cancer by Urinary Multimarker Sensor and Artificial Intelligence Analysis

Kim, H., Park, S., Jeong, I. G., Song, S. H., Jeong, Y., Kim, C.-S., & Lee, K. H. (2021) · ACS Nano · doi:10.1021/acsnano.0c06946 · Cited by 130 · see citing works

A Highly Aligned Nanowire‐Based Strain Sensor for Ultrasensitive Monitoring of Subtle Human Motion

Tang, N., Zhou, C. J., Qu, D., Fang, Y., Zheng, Y., Hu, W., Jin, K., Wu, W., Duan, X., & Haick, H. (2020) · Small · doi:10.1002/smll.202001363 · Cited by 114 · see citing works

Artificial intelligence-based clinical decision support in modern medical physics: Selection, acceptance, commissioning, and quality assurance

Mahadevaiah, G., RV, P., Bermejo, I., Jaffray, D., Dekker, A., & Wee, L. (2020) · Medical Physics · doi:10.1002/mp.13562 · Cited by 114 · see citing works

Detection of Breathing and Heart Rates in UWB Radar Sensor Data Using FVPIEF-Based Two-Layer EEMD

Shyu, K., Chiu, L.-J., Lee, P., Tung, T.-H., & Yang, S.-H. (2018) · IEEE Sensors Journal · doi:10.1109/jsen.2018.2878607 · Cited by 112 · see citing works

Tear Cytokine Profile as a Noninvasive Biomarker of Inflammation for Ocular Surface Diseases: Standard Operating Procedures

Wei, Y., Gadaria-Rathod, N., Epstein, S. P., & Asbell, P. A. (2013) · Investigative Ophthalmology & Visual Science · doi:10.1167/iovs.13-12132 · Cited by 99 · see citing works

Artificial Nose Technology: Status and Prospects in Diagnostics

Fitzgerald, J. E., Bui, É., Simon, N. M., & Fenniri, H. (2016) · Trends in biotechnology · doi:10.1016/j.tibtech.2016.08.005 · Cited by 94 · see citing works

Wearable Glove-Type Driver Stress Detection Using a Motion Sensor

Lee, B. G., & Chung, W. (2016) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2016.2617881 · Cited by 88 · see citing works

A Freestanding Stretchable and Multifunctional Transistor with Intrinsic Self‐Healing Properties of all Device Components

Khatib, M., Huynh, T., Deng, Y., Horev, Y. D., Saliba, W., Wu, W., & Haick, H. (2018) · Small · doi:10.1002/smll.201803939 · Cited by 85 · see citing works

Time-space-resolved origami hierarchical electronics for ultrasensitive detection of physical and chemical stimuli

Zhang, M., Sun, J. J., Khatib, M., Lin, Z., Chen, Z., Saliba, W., Gharra, A., Horev, Y. D., Kloper, V., Milyutin, Y., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-09070-8 · Cited by 84 · see citing works

Use of Electronic Noses for Diagnosis of Digestive and Respiratory Diseases through the Breath

Sánchez, C., Santos, J. P., & Lozano, J. (2019) · Biosensors · doi:10.3390/bios9010035 · Cited by 81 · see citing works

Future trends in the market for electrochemical biosensing

Neves, M. M. P. S., González-Garcı́a, M. B., Hernández‐Santos, D., & Fanjul‐Bolado, P. (2018) · Current Opinion in Electrochemistry · doi:10.1016/j.coelec.2018.05.002 · Cited by 80 · see citing works

Nonintrusive Monitoring of Mental Fatigue Status Using Epidermal Electronic Systems and Machine-Learning Algorithms

Zeng, Z., Huang, Z., Leng, K., Han, W., Niu, H., Yu, Y., Ling, Q., Liu, J., Wu, Z., & Zang, J. (2020) · ACS Sensors · doi:10.1021/acssensors.9b02451 · Cited by 79 · see citing works

A Fundamental-and-Harmonic Dual-Frequency Doppler Radar System for Vital Signs Detection Enabling Radar Movement Self-Cancellation

Zhu, F., Wang, K., & Wu, K. (2018) · IEEE Transactions on Microwave Theory and Techniques · doi:10.1109/tmtt.2018.2869591 · Cited by 52 · see citing works

Self‐Healable Materials for Underwater Applications

Huynh, T., Khatib, M., & Haick, H. (2019) · Advanced Materials Technologies · doi:10.1002/admt.201900081 · Cited by 51 · see citing works

WhatsApp embedded in routine service delivery for smoking cessation: effects on abstinence rates in a randomized controlled study

Durmaz, S., Ergin, I., Durusoy, R., Hassoy, H., Çalışkan, S. A., & Okyay, P. (2019) · BMC Public Health · doi:10.1186/s12889-019-6727-z · Cited by 50 · see citing works

Multi‐Parametric Sensing Platforms Based on Nanoparticles

Segev‐Bar, M., Bachar, N., Wolf, Y., Ukrainsky, B., Sarraf, L., & Haick, H. (2016) · Advanced Materials Technologies · doi:10.1002/admt.201600206 · Cited by 49 · see citing works

Toward an optimal use of artificial intelligence techniques within a clinical decision support system

Aljaaf, A. J., Al‐Jumeily, D., Hussain, A. J., Fergus, P., Al-Jumaily, M., & Abdel‐Aziz, K. (2015) · Science and Information Conference · doi:10.1109/sai.2015.7237196 · Cited by 48 · see citing works

Flexibility characteristics of a polyethylene terephthalate chemiresistor coated with a nanoparticle thin film assembly

Shan, S., Zhao, W., Luo, J., Yin, J., Switzer, J. C., Joseph, P., Lu, S. F., Poliks, M. D., & Zhong, C. (2014) · Journal of Materials Chemistry C · doi:10.1039/c3tc32332c · Cited by 44 · see citing works

Using Big Data and Predictive Analytics to Determine Patient Risk in Oncology

Parikh, R. B., Gdowski, A., Patt, D. A., Hertler, A. A., Mermel, C. H., & Bekelman, J. E. (2019) · American Society of Clinical Oncology Educational Book · doi:10.1200/edbk_238891 · Cited by 38 · see citing works

Biomedical sensors

Wan, H., Zhuang, L., Pan, Y., Gao, F., Tu, J., Zhang, B., & Wang, P. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-816034-3.00002-x · Cited by 26 · see citing works

Artificially Intelligent Nanoarray for the Detection of Preeclampsia under Real‐World Clinical Conditions

Nakhleh, M. K., Baram, S., Jeries, R., Salim, R., Haick, H., & Hakim, M. (2016) · Advanced Materials Technologies · doi:10.1002/admt.201600132 · Cited by 22 · see citing works

Interface‐Regulated Contact Electrification for Power‐Free and Highly Selective Gas Sensing

Wu, C., Liang, Y., Hu, W., Yuan, M., Bai, X., Liu, F., Zheng, Y., Zhao, Z., Zhang, M., Haick, H., et al. (2019) · Advanced Intelligent Systems · doi:10.1002/aisy.201900066 · Cited by 20 · see citing works

Contactless Radar Sensing for Health Monitoring

Fioranelli, F., & Kernec, J. L. (2020) · doi:10.1002/9781119644316.ch2 · Cited by 20 · see citing works

Comparative Analysis of Gait Speed Estimation Using Wideband and Narrowband Radars, Thermal Camera, and Motion Tracking Suit Technologies

Morita, P. P., Rocha, A. S., Shaker, G. S. A., Lee, D., Wei, J., Fong, B., Thatte, A., Karimi, A., Xu, L., Ma, A., et al. (2020) · Journal of Healthcare Informatics Research · doi:10.1007/s41666-020-00071-7 · Cited by 19 · see citing works

Smart device sensing architectures and applications

Dolui, K., Mukherjee, S., & Datta, S. K. (2013) · International Computer Science and Engineering Conference · doi:10.1109/icsec.2013.6694759 · Cited by 15 · see citing works

Digital health and patient‐centred care: A digital systems view

Papavasiliou, S., Reaiche, C. H., & Papavasiliou, S. (2020) · Systems Research and Behavioral Science · doi:10.1002/sres.2726 · Cited by 15 · see citing works

Implementation of intelligent decision support systems in health care

Smith, A. E., Nugent, C., & McClean, S. I. (2002) · Journal of Management in Medicine · doi:10.1108/02689230210434943 · Cited by 13 · see citing works

Health Information Tailoring and Data Privacy in a Smart Watch as a Preventive Health Tool

Yoon, H., Shin, D., & Kim, H. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-21006-3_51 · Cited by 11 · see citing works

Time‐Resolved and Self‐Adjusting Hybrid Functional Fabric Sensor for Decoupling Multiple Stimuli from Bending

Sun, J. J., Zhang, M., Khatib, M., Milyutin, Y., Saliba, W., Kloper, V., Garaa, A., Wu, W., Jin, H., Segev‐Bar, M., et al. (2019) · Advanced Materials Technologies · doi:10.1002/admt.201900290 · Cited by 9 · see citing works

Imaging of Human Walking Behind the Obstacle Utilizing Pulsed Radar Technique in the C-Band for Military Surveillance Applications

Lee, D., Shaker, G. S. A., & Melek, W. (2020) · Journal of Electrical Engineering and Technology · doi:10.1007/s42835-020-00405-w · Cited by 5 · see citing works

End-to-end design of wearable sensors

Ates, H. C., Nguyen, P. Q., Gonzalez-Macia, L., Morales-Narváez, E., Güder, F., Collins, J. J., & Dincer, C. (2022) · Nature Reviews Materials · doi:10.1038/s41578-022-00460-x · Cited by 1,306 · see citing works

Sensors for Volatile Organic Compounds

Khatib, M., & Haick, H. (2022) · ACS Nano · doi:10.1021/acsnano.1c10827 · Cited by 552 · see citing works

The emergence of AI-based wearable sensors for digital health technology: a review

Shajari, S., Kuruvinashetti, K., Komeili, A., & Sundararaj, U. (2023) · Sensors · doi:10.3390/s23239498 · Cited by 535 · see citing works

Age of Flexible Electronics: Emerging Trends in Soft Multifunctional Sensors

Lee, J., Cho, K., & Kim, J. (2024) · Advanced Materials · doi:10.1002/adma.202310505 · Cited by 367 · see citing works

Printable Smart Materials and Devices: Strategies and Applications

Su, M., & Song, Y. (2021) · Chemical Reviews · doi:10.1021/acs.chemrev.1c00303 · Cited by 312 · see citing works

Materials with Tunable Optical Properties for Wearable Epidermal Sensing in Health Monitoring

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Role of Machine Learning Assisted Biosensors in Point-of-Care-Testing For Clinical Decisions

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Electrochemical sensor for dopamine detection based on multiwalled carbon nanotube/molybdenum disulfide quantum dots with machine learning integration and anti-interference capability

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Photochromic properties of triangle terthiophene- and triphenylamine-configured diarylethene type dye with propeller-like conformation

Kong, Y., Liu, X., Jiang, W., & Li, X. (2025) · Chemical Papers · doi:10.1007/s11696-025-03934-8 · Cited by 16 · see citing works

Toward precision medicine: End-to-end design and construction of integrated microneedle-based theranostic systems

Qin, Y., Cui, F., Lu, Y., Yang, P., Gou, W., Tang, Z., Lu, S., Zhou, H. S., Luo, G., Lyu, X., et al. (2024) · Journal of Controlled Release · doi:10.1016/j.jconrel.2024.11.020 · Cited by 15 · see citing works

Advances and challenges in digitally connected point-of-care biosensing

Lahcen, A. A., Jegan, R., & Slaughter, G. (2025) · Biosensors and Bioelectronics X · doi:10.1016/j.biosx.2025.100728 · Cited by 15 · see citing works

Combinatorial AI and nanotechnological approaches for advancing medical sensors

Kapur, U., Adhikari, D., Tripathi, H., & Gabrani, R. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-45321-2.00003-5

Artificial Intelligence-Assisted Nanosensors for Clinical Diagnostics: Current Advances and Future Prospects

Yin, S. (2025) · Biosensors · doi:10.3390/bios15100656 · Cited by 54 · see citing works

Artificial Intelligence‐Based Medical Sensors for Healthcare System

Chen, M., Cui, D., Haick, H., & Tang, N. (2023) · Advanced Sensor Research · doi:10.1002/adsr.202300009 · Cited by 85 · see citing works

The emergence of AI-based wearable sensors for digital health technology: a review

Shajari, S., Kuruvinashetti, K., Komeili, A., & Sundararaj, U. (2023) · Sensors · doi:10.3390/s23239498 · Cited by 535 · see citing works

(Invited) Wearable Intelligent Sensors and Electronic (WISE)- Problem, Progress and Perspective

Xu, T., & Zhang, X. (2023) · ECS Meeting Abstracts · doi:10.1149/ma2023-02632976mtgabs