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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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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Histological diagnosis of unprocessed breast core-needle biopsy via stimulated Raman scattering microscopy and multi-instance learning

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CardioNet: a manually curated database for artificial intelligence-based research on cardiovascular diseases

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Novel approaches to targeting gliomas at the leading/cutting edge

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Intraoperative near infrared functional imaging of rectal cancer using artificial intelligence methods - now and near future state of the art

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The Duality of Raman Scattering

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Artificial Intelligence-Based Wearable Sensing Technologies for the Management of Cancer, Diabetes, and COVID-19

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Improved Diagnostic Imaging of Brain Tumors by Multimodal Microscopy and Deep Learning

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Fluorescence Lifetime Imaging and Spectroscopic Co-Validation for Protoporphyrin IX-Guided Tumor Visualization in Neurosurgery

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Slide Over

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Machine learning can aid in prediction of IDH mutation from H&E-stained histology slides in infiltrating gliomas

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In vivo characterization of the human glioblastoma infiltrative edge with label-free intraoperative fluorescence lifetime imaging

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Current Landscape of Advanced Imaging Tools for Pathology Diagnostics

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A systematic review on deep learning implementation in brain tumor segmentation, classification and prediction

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Automated histologic diagnosis of CNS tumors with machine learning

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The diagnostic accuracy of intraoperative differentiation and delineation techniques in brain tumours

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Background signals in stimulated Raman scattering microscopy and current solutions to avoid them

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Intraoperative microscopic autofluorescence detection and characterization in brain tumors using stimulated Raman histology and two-photon fluorescence

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FAP-catalyzed in situ self-assembly of magnetic resonance imaging probe for early and precise staging of liver fibrosis

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Simultaneous stimulated Raman gain and loss detection (SRGAL)

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An efficient approach to diagnose brain tumors through deep CNN

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Metabolic profiles of human brain parenchyma and glioma for rapid tissue diagnosis by targeted desorption electrospray ionization mass spectrometry

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Diagnostics and theranostics of central nervous system diseases based on aggregation-induced emission luminogens

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Raman spectroscopy: A prospective intraoperative visualization technique for gliomas

Zhang, Y., Yu, H., Li, Y., Xu, H., Yang, L., Shan, P., Du, Y., Yan, X., & Chen, X. (2023) · Frontiers in Oncology · doi:10.3389/fonc.2022.1086643 · Cited by 24

The leading global health challenges in the artificial intelligence era

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Virtual Staining of Nonfixed Tissue Histology

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CORR Synthesis: When Should the Orthopaedic Surgeon Use Artificial Intelligence, Machine Learning, and Deep Learning?

Murphy, M. P., & Brown, N. M. (2021) · Clinical Orthopaedics and Related Research · doi:10.1097/corr.0000000000001679 · Cited by 25

Encoding histopathology whole slide images with location-aware graphs for diagnostically relevant regions retrieval

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An Acidity-Initiated Self-Assembly/Disassembly Nanoprobe to Switch on Fluorescence for Tumor-Targeted Near-Infrared Imaging

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Raman Spectroscopy: A Tool for Molecular Fingerprinting of Brain Cancer

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Towards integration of artificial intelligence into medical devices as a real-time recommender system for personalised healthcare: State-of-the-art and future prospects

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Technical report: surgical preparation of human brain tissue for clinical and basic research

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SMART on FHIR in spine: integrating clinical prediction models into electronic health records for precision medicine at the point of care

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AI in Measurement Science

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Deep-learning based classification distinguishes sarcomatoid malignant mesotheliomas from benign spindle cell mesothelial proliferations

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BOLD asynchrony elucidates tumor burden in IDH-mutated gliomas

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Shot-noise limited tunable dual-vibrational frequency stimulated Raman scattering microscopy

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Multiplex Identification of Post‐Translational Modifications at Point‐of‐Care by Deep Learning‐Assisted Hydrogel Sensors

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Hierarchical Discriminative Learning Improves Visual Representations of Biomedical Microscopy

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A clinically applicable AI system for diagnosis of congenital heart diseases based on computed tomography images

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Deep-Learning–Based Screening and Ancillary Testing for Thyroid Cytopathology

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Lung Cancer Diagnosis on Virtual Histologically Stained Tissue Using Weakly Supervised Learning

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Pinpointing Fat Molecules: Advances in Coherent Raman Scattering Microscopy for Lipid Metabolism

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Artificial intelligence-aided data mining of medical records for cancer detection and screening

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Context aware machine learning techniques for brain tumor classification and detection – A review

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The Role of Stereotactic Biopsy in Brain Metastases

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Digital Technology: Key considerations for the use of artificial intelligence in healthcare and clinical research

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Precise Identification of Glioblastoma Micro‐Infiltration at Cellular Resolution by Raman Spectroscopy

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Serum metabolic profiling enables diagnosis, prognosis, and monitoring for brainstem gliomas

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Category guided attention network for brain tumor segmentation in MRI

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Rapid ultraviolet photoacoustic remote sensing microscopy using voice-coil stage scanning

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An automated tissue-to-diagnosis pipeline using intraoperative stimulated Raman histology and deep learning

Hollon, T. C., & Orringer, D. A. (2020) · Molecular & Cellular Oncology · doi:10.1080/23723556.2020.1736742 · Cited by 20

Label-free histological imaging of tissues using Brillouin light scattering contrast

Ryu, S., Martino, N., Kwok, S. J. J., Bernstein, L., & Yun, S. H. (2021) · Biomedical Optics Express · doi:10.1364/boe.414474 · Cited by 24

Stimulated Raman Histology Interpretation by Artificial Intelligence Provides Near-Real-Time Pathologic Feedback for Unprocessed Prostate Biopsies

Mannas, M. P., Deng, F. M., Ion‐Mărgineanu, A., Jones, D., Hoskoppal, D., Melamed, J., Pastore, S., Freudiger, C. W., Orringer, D. A., & Taneja, S. S. (2023) · The Journal of Urology · doi:10.1097/ju.0000000000003811 · Cited by 20

A novel approach for the detection of brain tumor and its classification via end-to-end vision transformer - CNN architecture

Chandraprabha, K. S., Ganesan, L., & Baskaran, K. (2025) · Frontiers in Oncology · doi:10.3389/fonc.2025.1508451 · Cited by 20

Advancing gene therapies, methods, and technologies for Parkinson’s Disease and other neurological disorders

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Towards interpretable imaging genomics analysis: Methodological developments and applications

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Intraoperative margin assessment for basal cell carcinoma with deep learning and histologic tumor mapping to surgical site

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High-content stimulated Raman histology of human breast cancer

Ni, H., Dessai, C. V. P., Lin, H., Wang, W., Chen, S., Yuan, Y., Ge, X., Ao, J., Vild, N., & Cheng, J. (2024) · Theranostics · doi:10.7150/thno.90336 · Cited by 19

Optical-resolution parallel ultraviolet photoacoustic microscopy for slide-free histology

Cao, R., Luo, Y., Zhao, J., Zeng, Y., Zhang, Y., Zhou, Q., de la Zerda, A., & Wang, L. V. (2024) · Science Advances · doi:10.1126/sciadv.ado0518 · Cited by 19

Fast intraoperative detection of primary central nervous system lymphoma and differentiation from common central nervous system tumors using stimulated Raman histology and deep learning

Reinecke, D., Maarouf, N., Smith, A., Alber, D. A., Markert, J. E., Goff, N. K., Hollon, T. C., Chowdury, A., Jiang, C., Hou, X., et al. (2024) · Neuro-Oncology · doi:10.1093/neuonc/noae270 · Cited by 19

Intraoperative brain tumour identification with deep learning

Martini, M. L., & Oermann, E. K. (2020) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-020-0343-9 · Cited by 20

Performance of deep learning algorithms to distinguish high-grade glioma from low-grade glioma: A systematic review and meta-analysis

Sun, W., Song, C., Tang, C., Pan, C., Xue, P., Fan, J., & Qiao, Y. (2023) · iScience · doi:10.1016/j.isci.2023.106815 · Cited by 21

Stimulated Raman histology, a novel method to allow for rapid pathologic examination of unprocessed, fresh prostate biopsies

Mannas, M. P., Jones, D., Deng, F., Hoskoppal, D., Melamed, J., Orringer, D. A., & Taneja, S. S. (2023) · The Prostate · doi:10.1002/pros.24547 · Cited by 19

Stain-Free Histopathology with Stimulated Raman Scattering Microscopy

Ma, L., Luo, K., Liu, Z., & Ji, M. (2024) · Analytical Chemistry · doi:10.1021/acs.analchem.4c02061 · Cited by 18

Raman-based machine-learning platform reveals unique metabolic differences between IDHmut and IDHwt glioma

Lita, A., Sjöberg, J., Păcioianu, D., Siminea, N., Celiku, O., Dowdy, T., Păun, A., Gilbert, M. R., Noushmehr, H., Petre, I., et al. (2024) · Neuro-Oncology · doi:10.1093/neuonc/noae101 · Cited by 21

Metastatic brain tumors: from development to cutting‐edge treatment

Tanzhu, G., Chen, L., Ning, J., Xue, W., Wang, C., Xiao, G., Yang, J., & Zhou, R. (2024) · MedComm · doi:10.1002/mco2.70020 · Cited by 19

Review of Laser Raman Spectroscopy for Surgical Breast Cancer Detection: Stochastic Backpropagation Neural Networks

Kothari, R., Fong, Y., & Storrie‐Lombardi, M. C. (2020) · Sensors · doi:10.3390/s20216260 · Cited by 19

Rapid Intraoperative Diagnosis of Meningiomas using Stimulated Raman Histology

Di, L., Eichberg, D. G., Park, Y. J., Shah, A. H., Jamshidi, A. M., Luther, E., Lu, V. M., Komotar, R. J., Ivan, M. E., & Gultekin, S. H. (2021) · World Neurosurgery · doi:10.1016/j.wneu.2021.02.097 · Cited by 19

Uncertainty-aware ensemble of foundation models differentiates glioblastoma from its mimics

Zhao, J., Lin, S.-Y., Attias, R., Mathews, L., Engel, C., Larghero, G., Vremenko, D., Kao, T., Lee, T.-H., Wang, Y.-H., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-64249-6 · Cited by 21

A Brief History of Machine Learning in Neurosurgery

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Novel intraoperative strategies for enhancing tumor control: Future directions

Haddad, A. F., Aghi, M. K., & Butowski, N. A. (2022) · Neuro-Oncology · doi:10.1093/neuonc/noac090 · Cited by 18

Opportunities of optical and spectral technologies in intraoperative histopathology

Krafft, C., & Popp, J. (2022) · Optica · doi:10.1364/optica.478211 · Cited by 18

Clinical Validation of Stimulated Raman Histology for Rapid Intraoperative Diagnosis of Central Nervous System Tumors

Movahed-Ezazi, M., Nasir-Moin, M., Fang, C. S., Pizzillo, I., Galbraith, K., Drexler, S. A., Krasnozhen-Ratush, O., Shroff, S., Zagzag, D., William, C. M., et al. (2023) · Modern Pathology · doi:10.1016/j.modpat.2023.100219 · Cited by 18

Deep learning provides high accuracy in automated chondrocyte viability assessment in articular cartilage using nonlinear optical microscopy

Chen, X., Li, Y., Wyman, N., Zhang, Z., Fan, H., Le, M., Gannon, S., Rose, C., Zhang, Z., Mercuri, J. J., et al. (2021) · Biomedical Optics Express · doi:10.1364/boe.417478 · Cited by 17

Non-invasive cell classification using the Paint Raman Express Spectroscopy System (PRESS)

Akagi, Y., Mori, N., Kawamura, T., Takayama, Y., & Kida, Y. S. (2021) · Scientific Reports · doi:10.1038/s41598-021-88056-3 · Cited by 18

Raman Spectroscopy as a Neuromonitoring Tool in Traumatic Brain Injury: A Systematic Review and Clinical Perspectives

Stevens, A. R., Stickland, C. A., Harris, G., Ahmed, Z., Oppenheimer, P. G., Belli, A., & Davies, D. (2022) · Cells · doi:10.3390/cells11071227 · Cited by 16

Artificial intelligence guided Raman spectroscopy in biomedicine: Applications and prospects

Liu, Y., Chen, S., Xiong, X., Wen, Z., Zhao, L., Xu, B., Guo, Q., Xia, J., & Pei, J. (2025) · Journal of Pharmaceutical Analysis · doi:10.1016/j.jpha.2025.101271 · Cited by 22

Neural Networks-Based On-Site Dermatologic Diagnosis through Hyperspectral Epidermal Images

Salvia, M. L., Torti, E., León, R., Fabelo, H. A., Ortega, S., Balea-Fernandez, F., Martinez-Vega, B., Castaño, I., Almeida, P., Carretero, G., et al. (2022) · Sensors · doi:10.3390/s22197139 · Cited by 17

Ag@C decorated GaN nanoflower enabled super-stable, single molecule level SERS substrate integrated with machine learning for multiple analytes identification

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Machine Learning in Bioelectrocatalysis

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