Near real-time intraoperative brain tumor diagnosis using stimulated Raman histology and deep neural networks

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Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

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Visualizing and understanding convolutional networks

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The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary

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The 2007 WHO Classification of Tumours of the Central Nervous System

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Dermatologist-level classification of skin cancer with deep neural networks

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CBTRUS Statistical Report: Primary Brain and Central Nervous System Tumors Diagnosed in the United States in 2006-2010

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High-performance medicine: the convergence of human and artificial intelligence

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Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs

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A ratiometric SERS strategy for the prediction of cancer cell proportion and guidance of glioma surgical resection

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Recent progress in plasmonic nanoparticle‐based biomarker detection and cytometry for the study of central nervous system disorders

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OCT2Hist: Non-Invasive Virtual Biopsy Using Optical Coherence TomographyPreprint

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Determinants of climate change adaptation strategies among rural household farmers in the Wolaita zone, Southern Ethiopia

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Histopathological-based brain tumor grading using 2D-3D multi-modal CNN-transformer combined with stacking classifiers

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AI-Based Detection of Oral Squamous Cell Carcinoma with Raman Histology

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Extent of Resection Thresholds in Molecular Subgroups of Newly Diagnosed Isocitrate Dehydrogenase–Wildtype Glioblastoma

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In vivo organoid growth monitoring by stimulated Raman histology

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Transformative applications of oculomics-based AI approaches in the management of systemic diseases: A systematic review

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Machine Learning and Artificial Intelligence Systems Based on the Optical Spectral Analysis in Neuro-Oncology

Savelieva, T. A., Romanishkin, I. D., Ospanov, A., Goryaynov, S. A., Pavlova, G. V., Pronin, I., & Loschenov, V. B. (2025) · Photonics · doi:10.3390/photonics12010037 · Cited by 14

Tumor-Homing Biomimetic Near-Infrared II SERS Probes for Targeted Intraoperative Resection Guidance of Orthotopic Glioblastoma

Lu, Y., Shan, B., Li, L., Jiang, R., & Li, M. (2025) · Nano Letters · doi:10.1021/acs.nanolett.4c05622 · Cited by 14

A deep learning model designed for Raman spectroscopy with a novel hyperparameter optimization method

Sui, A., Deng, Y., Wang, Y., & Yu, J. (2022) · Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy · doi:10.1016/j.saa.2022.121560 · Cited by 14

AI in Health Science: A Perspective

Mishra, R., Chaudhary, K., & Mishra, I. (2022) · Current Pharmaceutical Biotechnology · doi:10.2174/1389201023666220929145220 · Cited by 14

AI-assisted SERS imaging method for label-free and rapid discrimination of clinical lymphoma

Cao, H., Wu, X., Shi, H., Chu, B., He, Y., Wang, H., & Dong, F. (2025) · Journal of Nanobiotechnology · doi:10.1186/s12951-025-03339-5 · Cited by 13

Advanced deep learning-based brain tumor classification using a novel customized CNN and optimized residual network

Rasheed, M., Iqbal, S., Jaffar, A., & Akram, S. (2025) · PLoS ONE · doi:10.1371/journal.pone.0334430 · Cited by 13

Optical spectroscopy and imaging in surgical management of cancer patients

Wilson, B. C., & Eu, D. (2022) · Translational Biophotonics · doi:10.1002/tbio.202100009 · Cited by 13

Advances in Biomedical Applications of Raman Microscopy and Data Processing: A Mini Review

Krishna, R., & Çolak, İ. (2022) · Analytical Letters · doi:10.1080/00032719.2022.2094391 · Cited by 13

Advances in the intraoperative delineation of malignant glioma margin

Jiang, S., Chai, H., & Tang, Q. (2023) · Frontiers in Oncology · doi:10.3389/fonc.2023.1114450 · Cited by 13

Stimulated Raman histology for histological evaluation of oral squamous cell carcinoma

Steybe, D., Poxleitner, P. J., Metzger, M. C., Rothweiler, R. M., Beck, J., Straehle, J., Vach, K., Weber, A. T., Enderle-Ammour, K., Werner, M., et al. (2023) · Clinical Oral Investigations · doi:10.1007/s00784-023-05098-9 · Cited by 13

Accelerating Cancer Histopathology Workflows with Chemical Imaging and Machine Learning

Falahkheirkhah, K., Mukherjee, S. S., Gupta, S., Herrera-Hernandez, L. P., McCarthy, M. R., Jiménez, R. E., Cheville, J. C., & Bhargava, R. (2023) · Cancer Research Communications · doi:10.1158/2767-9764.crc-23-0226 · Cited by 14

Accurate MRI-Based Brain Tumor Diagnosis: Integrating Segmentation and Deep Learning Approaches

Ashimgaliyev, M., Matkarimov, B. T., Barlybayev, A., Li, R. Y. M., & Zhumadillayeva, А. (2024) · Applied Sciences · doi:10.3390/app14167281 · Cited by 13

Explainable biology for improved therapies in precision medicine: AI is not enough

Jurišica, I. (2024) · Best Practice & Research Clinical Rheumatology · doi:10.1016/j.berh.2024.102006 · Cited by 13

Liver segmentation network based on detail enhancement and multi-scale feature fusion

Tinglan, L., Qin, J., Guihe, Q., Shi, W., & Zhang, W. (2025) · Scientific Reports · doi:10.1038/s41598-024-78917-y · Cited by 13

Integration of Raman spectra with transcriptome data in glioblastoma multiforme defines tumour subtypes and predicts patient outcome

Reste, P. L., Pilalis, E. D., Aubry, M., McMahon, M., Cano, L., Etcheverry, A., Chatziioannou, A. A., Chevet, É., & Fautrel, A. (2021) · Journal of Cellular and Molecular Medicine · doi:10.1111/jcmm.16902 · Cited by 13

Stimulated Raman histology facilitates accurate diagnosis in neurosurgical patients: a one-to-one noninferiority study

Einstein, E. H., Ablyazova, F., Rosenberg, A., Harshan, M., Wahl, S. J., Har‐El, G., Constantino, P. D., Ellis, J. A., Boockvar, J. A., Langer, D. J., et al. (2022) · Journal of Neuro-Oncology · doi:10.1007/s11060-022-04071-y · Cited by 13

Stimulated Raman scattering microscopy on biological cellular machinery

Huang, J., & Ji, M. (2022) · Journal of Innovative Optical Health Sciences · doi:10.1142/s1793545822300105 · Cited by 13

Artificial intelligence-enhanced intraoperative neurosurgical workflow: current knowledge and future perspectives

Tariciotti, L., Palmisciano, P., GIORDANO, M., REMOLI, G., LACORTE, E., Bertani, G., Locatelli, M., DIMECO, F., Caccavella, V. M., & PRADA, F. (2021) · Journal of Neurosurgical Sciences · doi:10.23736/s0390-5616.21.05483-7 · Cited by 16

Advanced intraoperative MRI in pediatric brain tumor surgery

Jellema, P. E. J., Wijnen, J. P., Luca, A. D., Mutsaerts, H. J. M. M., Obdeijn, I. V., van Baarsen, K. M., Lequin, M. H., & Hoving, E. W. (2023) · Frontiers in Physiology · doi:10.3389/fphys.2023.1098959 · Cited by 12

Noninvasive Nonlinear Optical Computational Histology

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Artificial Intelligence and Deep Learning in Revolutionizing Brain Tumor Diagnosis and Treatment: A Narrative Review

Mandal, S., Chakraborty, S., Tariq, M. A., Ali, K., Elavia, Z. A., Khan, M. K., Garcia, D. B., Ali, S., Hooti, J. A., & Kumar, D. V. (2024) · Cureus · doi:10.7759/cureus.66157 · Cited by 14

Ultrabright contrast agents with synergistic Raman enhancements for precise intraoperative imaging and photothermal ablation of orthotopic tumor models

Ma, Y., Xia, S., Hu, A., Zhang, Q., Shao, Z., Tian, B., & Lin, Q. (2025) · Journal of Nanobiotechnology · doi:10.1186/s12951-025-03099-2 · Cited by 12

Intraoperative classification of CNS lymphoma and glioblastoma by AI-based analysis of Stimulated Raman Histology (SRH)

Scheffler, P., Straehle, J., Rahal, A. E., Erny, D., Mizaikoff, B., Vasilikos, I., Prinz, M., Coenen, V. A., Kühn, J., Scherer, F., et al. (2025) · Brain and Spine · doi:10.1016/j.bas.2025.104187 · Cited by 13

Cognitive Computing-Based CDSS in Medical Practice

Chen, J., Lu, C., Huang, H., Zhu, D., Yang, Q., Liu, J., Huang, Y., Deng, A., & Han, X. (2021) · Health Data Science · doi:10.34133/2021/9819851 · Cited by 13

In vivo simultaneous nonlinear absorption Raman and fluorescence (SNARF) imaging of mouse brain cortical structures

Francis, A. T., Manifold, B., Carlson, E. C., Hu, R., Hill, A. H., Men, S., & Fu, D. (2022) · Communications Biology · doi:10.1038/s42003-022-03166-6 · Cited by 11

Five-Year Prognosis Model of Esophageal Cancer Based on Genetic Algorithm Improved Deep Neural Network

Sun, J., Liu, Q., Wang, Y., Wang, L., Song, X., & Zhao, X. (2023) · IRBM · doi:10.1016/j.irbm.2022.100748 · Cited by 12

Rapid azoospermia classification by stimulated Raman scattering and second harmonic generation microscopy

Jie, H. J., Tang, X., Chen, Z., Li, X., Zhang, Y., Huang, X., Zhang, D., An, G., & Lee, H. J. (2023) · Biomedical Optics Express · doi:10.1364/boe.501623 · Cited by 12

Feasibility of a Randomized Controlled Trial of Large AI-Based Linguistic Models for Clinical Reasoning Training of Physical Therapy Students: Pilot Randomized Parallel-Group Study

Peña, R. F., Di‐Bonaventura, S., Gonzalez, A., & Calvo, A. L. (2025) · JMIR Formative Research · doi:10.2196/66126 · Cited by 11

Intraoperative pathological diagnosis for breast cancer with a polarity fluorescent probe targeting lipid droplets

Meng, F., Lyu, Q., Zhu, W., He, J., Gao, P., Gao, L., & Yu, X. (2025) · Sensors and Actuators B Chemical · doi:10.1016/j.snb.2025.138305 · Cited by 11

Light and metabolism: label-free optical imaging of metabolic activities in biological systems [Invited]

Menozzi, L., Li, Z., Choi, S., Vu, T., Shi, L., & Yao, J. (2025) · Biomedical Optics Express · doi:10.1364/boe.572304 · Cited by 13

Artificial intelligence and machine learning approaches for patient safety in complex surgery: a review

Ahmed, M. M., Othman, Z. K., Adebayo, U. O., Kasimieh, O., Okesanya, O. J., Musa, S. S., Branda, F., Cañezo, V. C., Cue, E. G., & Lucero‐Prisno, D. E. (2025) · Patient Safety in Surgery · doi:10.1186/s13037-025-00458-8 · Cited by 11

Diagnosing Hirschsprung disease by detecting intestinal ganglion cells using label-free hyperspectral microscopy

de Oliveira, M. A. S., Galganski, L. A., Stokes, S. C., Chang, C. W., Pivetti, C. D., Zhang, B., Matsukuma, K. E., Saadai, P., & Chan, J. W. (2021) · Scientific Reports · doi:10.1038/s41598-021-80981-7 · Cited by 11

Quantitative Chemical Imaging of Bone Tissue for Intraoperative and Diagnostic Applications

Shin, K. S., Men, S., Wong, A., Cobb-Bruno, C., Chen, E. Y., & Fu, D. (2022) · Analytical Chemistry · doi:10.1021/acs.analchem.1c04354 · Cited by 11

Deep learning-based high-speed, large-field, and high-resolution multiphoton imaging

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Attention‐guided multi‐scale context aggregation network for multi‐modal brain glioma segmentation

Wu, S., Cao, Y., Li, X., Liu, Q., Ye, Y., Liu, X., Zeng, L., & Tian, M. (2023) · Medical Physics · doi:10.1002/mp.16452 · Cited by 11

Brain tumour detection from magnetic resonance imaging using convolutional neural networks

Rethemiotaki, I. (2023) · Współczesna Onkologia · doi:10.5114/wo.2023.135320 · Cited by 11

Computational modeling for medical data: From data collection to knowledge discovery

Yin, Y., Xu, S., Hong, Y., Cai, Y., Tang, W., Wang, J., Shen, B., Zong, H., & Yu, G. (2024) · The Innovation Life · doi:10.59717/j.xinn-life.2024.100079 · Cited by 11

Artificial intelligence to assist decision-making on pharmacotherapy: A feasibility study

Bücker, M., Hoti, K., & Rose, O. (2024) · Exploratory Research in Clinical and Social Pharmacy · doi:10.1016/j.rcsop.2024.100491 · Cited by 11

Deep learning-driven macroscopic AI segmentation model for brain tumor detection via digital pathology: Foundations for terahertz imaging-based AI diagnostics

Yim, M. S., Kim, Y. H., Bark, H. S., Oh, S. J., Maeng, I., Shim, J., Chang, J. H., Kang, S., Yoo, B. C., Kwon, J. G., et al. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e40452 · Cited by 11

Artificial Intelligence-Assisted Stimulated Raman Histology: New Frontiers in Vibrational Tissue Imaging

Nambudiri, M. K. K., Sujadevi, V. G., Poornachandran, P., Krishna, C. M., Kanno, T., & Noothalapati, H. (2024) · Cancers · doi:10.3390/cancers16233917 · Cited by 13

Ultra-Rapid Droplet Digital PCR Enables Intraoperative Tumor Quantification

Murphy, Z. R., Bianchini, E. C., Smith, A., Wadiura, L. I., Russell, T., Reinecke, D., Maarouf, N., Wang, Y., Golfinos, J. G., Miller, A. M., et al. (2024) · Med · doi:10.1016/j.medj.2025.100604 · Cited by 11

A comparative study of explainability methods for whole slide classification of lymph node metastases using vision transformers

Rahnfeld, J., Naouar, M., Kalweit, G., Boedecker, J., Dubruc, E., & Kalweit, G. (2025) · PLOS Digital Health · doi:10.1371/journal.pdig.0000792 · Cited by 14

Random splicing assisted deep learning for breast cancer cell line classification via Raman spectroscopy

Liu, Y., Liu, J.-F., Wan, J., Hao, H., Liu, G., & Huang, X. (2025) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2025.05.051 · Cited by 11

Initial Evaluation of Rapid, Direct-to-Digital Prostate Biopsy Pathology

Torres, R., Olson, E. M., Homer, R., Martin, D. T., Levene, M. J., Perincheri, S., Sprenkle, P. C., & Humphrey, P. A. (2020) · Archives of Pathology & Laboratory Medicine · doi:10.5858/arpa.2020-0037-oa · Cited by 11

Label-free detection of brain tumors in a 9L gliosarcoma rat model using stimulated Raman scattering-spectroscopic optical coherence tomography

Soltani, S., Guang, Z., Zhang, Z., Olson, J. J., & Robles, F. E. (2021) · Journal of Biomedical Optics · doi:10.1117/1.jbo.26.7.076004 · Cited by 11

Stimulated Raman Histology for Rapid Intra‐Operative Diagnosis of Sinonasal and Skull Base Tumors

Fitzgerald, C. W. R., Doğan, S., Nassif, R. B., Mclean, T., Woods, R., Cracchiolo, J. R., Ganly, I., Tabar, V. S., & Cohen, M. A. (2022) · The Laryngoscope · doi:10.1002/lary.30233 · Cited by 11

OpenSRH: optimizing brain tumor surgery using intraoperative stimulated Raman histology

Jiang, C., Chowdury, A., Hou, X., Kondepudi, A., Freudiger, C. W., Conway, K. S., Camelo-Piragua, S. I., Orringer, D. A., Lee, H., & Hollon, T. C. (2022) · PubMed · doi:10.48550/arxiv.2206.08439 · Cited by 11

Machine learning in neuro-oncology: toward novel development fields

Nunno, V. D., Fordellone, M., Minniti, G. C., Asioli, S., Conti, A., Mazzatenta, D., Balestrini, D., Chiodini, P., Agati, R., Tonon, C., et al. (2022) · Journal of Neuro-Oncology · doi:10.1007/s11060-022-04068-7 · Cited by 11

Neurosurgical Management of Cerebrospinal Tumors in the Era of Artificial Intelligence : A Scoping Review

Agadi, K., Dominari, A., Tebha, S. S., Mohammadi, A., & Zahid, S. (2022) · Journal of Korean Neurosurgical Society · doi:10.3340/jkns.2021.0213 · Cited by 11

Toward intraoperative tissue classification: exploiting signal feedback from an ultrasonic aspirator for brain tissue differentiation

Bockelmann, N., Schetelig, D., Kesslau, D., Buschschlüter, S., Ernst, F., & Bonsanto, M. M. (2022) · International Journal of Computer Assisted Radiology and Surgery · doi:10.1007/s11548-022-02713-0 · Cited by 11

Innovations in the Diagnosis and Surgical Management of Low-Grade Gliomas

Uribe-Cardenas, R., Giantini-Larsen, A., Garton, A. L. A., Juthani, R. G., & Schwartz, T. H. (2022) · World Neurosurgery · doi:10.1016/j.wneu.2022.06.070 · Cited by 11

Polysulfide Serves as a Hallmark of Desmoplastic Reaction to Differentially Diagnose Ductal Carcinoma In Situ and Invasive Breast Cancer by SERS Imaging

Kubo, A., Masugi, Y., Hase, T., Nagashima, K., Kawai, Y., Takizawa, M., Hishiki, T., Shiota, M., Wakui, M., Kitagawa, Y., et al. (2023) · Antioxidants · doi:10.3390/antiox12020240 · Cited by 11

Demonstration of graphene-assisted tunable surface plasmonic resonance sensor using machine learning model

Rastogi, K., Sharma, A. K., & Prajapati, Y. K. (2023) · Applied Physics A · doi:10.1007/s00339-023-06630-0 · Cited by 11

From Research to Diagnostic Application of Raman Spectroscopy in Neurosciences: Past and Perspectives

Klamminger, G. G., Frauenknecht, K. B. M., Mittelbronn, M. G. A., & Borgmann, F. B. K. (2022) · Free Neuropathology · doi:10.17879/freeneuropathology-2022-4210 · Cited by 10

Assessment of Glial Fibrillary Acidic Protein Binding to the Surface of Leukocytes with Dark‐Field Imaging and Computational Analysis

Peng, F., Jeong, S., González, G., Marks, H. L., Ho, A., Roussakis, E., Krauledat, P. B., Hansen, P., & Evans, C. L. (2021) · Advanced Functional Materials · doi:10.1002/adfm.202009229 · Cited by 11

ROAM: Random layer mixup for semi‐supervised learning in medical images

Bdair, T. M., Wiestler, B., Navab, N., & Albarqouni, S. (2022) · IET Image Processing · doi:10.1049/ipr2.12511 · Cited by 11

Advances in cancer biomarkers: current detection strategies and challenges

Liu, Z., Huang, Z., Chen, X., Zhang, L., Wu, Q. D., Li, L., Yu, C., & Wei, J. (2025) · Coordination Chemistry Reviews · doi:10.1016/j.ccr.2025.217242 · Cited by 10

Artificial Intelligence in Surgery, Surgical Subspecialties, and Related Disciplines

Lee, R. Y., Ziehm, A. I., Ullrich, L. A., & Stawicki, S. P. (2023) · Artificial intelligence · doi:10.5772/intechopen.112691 · Cited by 10

EAN: enhanced AlexNet deep learning model to detect brain tumor using magnetic resonance images

Azhagiri, M., & Rajesh, P. (2024) · Multimedia Tools and Applications · doi:10.1007/s11042-024-18143-w · Cited by 10

Fast Real-Time Brain Tumor Detection Based on Stimulated Raman Histology and Self-Supervised Deep Learning Model

Wang, Z., Han, K., Liu, W., Wang, Z., Shi, C., Liu, X., Huang, M., Sun, G., Liu, S., & Guo, Q. (2024) · Journal of Imaging Informatics in Medicine · doi:10.1007/s10278-024-01001-4 · Cited by 10

Label‐Free Virtual Peritoneal Lavage Cytology via Deep‐Learning‐Assisted Single‐Color Stimulated Raman Scattering Microscopy

Fang, T., Wu, Z., Chen, X., Tan, L., Li, Z., Ji, J., Fan, Y., Li, Z., & Yue, S. (2024) · Advanced Intelligent Systems · doi:10.1002/aisy.202300689 · Cited by 10

Intraoperative label-free tissue diagnostics using a stimulated Raman histology imaging system with artificial intelligence: An initial experience

Nohman, A. I., Ivren, M., Alhalabi, O., Sahm, F., Trong, P. D., Krieg, S. M., Unterberg, A. W., & Scherer, M. (2024) · Clinical Neurology and Neurosurgery · doi:10.1016/j.clineuro.2024.108646 · Cited by 10

Unmixing Autoencoder for Image Reconstruction from Hyperspectral Data

Liu, X., Duan, C., Cai, W., & Shao, X. (2024) · Analytical Chemistry · doi:10.1021/acs.analchem.4c02720 · Cited by 10

Molecular-based decision-making in glioblastoma surgery: When to aim for supramaximal resection

Drexler, R., Lim, M. K., & Hervey‐Jumper, S. L. (2025) · Neuro-Oncology · doi:10.1093/neuonc/noaf062 · Cited by 11

Classification of Soft Tissue Sarcoma Specimens with Raman Spectroscopy as Smart Sensing Technology

Li, L., Mustahsan, V. M., He, G., Tavernier, F. B., Singh, G., Boyce, B. F., Khan, F. A., & Kao, I. (2021) · Cyborg and Bionic Systems · doi:10.34133/2021/9816913 · Cited by 10

A semantic segmentation model for lumbar MRI images using divergence loss

Hou, C., Zhang, W., Wang, H., Liu, F., Liu, D., & Chang, J. (2022) · Applied Intelligence · doi:10.1007/s10489-022-04118-7 · Cited by 10

Study protocol: retrospectively mining multisite clinical data to presymptomatically predict seizure onset for individual patients with Sturge-Weber

Vedmurthy, P., Pinto, A., Lin, D. D. M., Comi, A. M., & Ou, Y. (2022) · BMJ Open · doi:10.1136/bmjopen-2021-053103 · Cited by 10

Early repeat resection for residual glioblastoma: decision-making among an international cohort of neurosurgeons

Kim, A. A., Dono, A., Khalafallah, A. M., Nettel-Rueda, B., Samandouras, G., Hadjipanayis, C. G., Mukherjee, D. R., & Esquenazi, Y. (2022) · Journal of neurosurgery · doi:10.3171/2022.1.jns211970 · Cited by 10

Optofluidic identification of single microorganisms using fiber‐optical‐tweezer‐based Raman spectroscopy with artificial neural network

Lin, C., Li, X., Wu, T., Xu, J., Gong, Z., Chen, T., Li, B., Li, Y., Guo, J., & Zhang, Y. (2023) · BMEMat · doi:10.1002/bmm2.12007 · Cited by 10

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