Hyperspectral In-Memory Computing with Optical Frequency Combs and Programmable Optical Memories

Physics, Electromagnetism, Optics, Engineering, Electrical Engineering, Information Science, Electronic Information, Semiconductors and Information Devices,
hyperspectral   optical frequency combs   in-memory computing   optical computing   matrix multiplication  

Hyperspectral In-Memory Computing and Applications of Optical Frequency Comb and Programmable Optical Memory Introduction In recent years, breakthroughs in machine learning have driven revolutionary developments in various industries, including healthcare, finance, retail, automotive, and manufacturing. These transformations have led to a surge in ...

Mode-locked Waveguide Polariton Laser

Physics, Optics, Quantum Physics, Information Science, Semiconductors and Information Devices,
mode-locking   waveguide   polariton laser   exciton-polariton   non-linear optics   self-phase modulation   soliton  

Research Report on the Realization of Blue-Ultraviolet Light Mode-Locking by Polariton Waveguides In the field of modern optoelectronics, continuous advancements in laser technology have greatly propelled the development of information technology, biomedicine, and industrial processing, among other sectors. Mode-locked laser technology, in particul...

Tumor Size Is Not Everything: Advancing Radiomics as a Precision Medicine Biomarker in Oncology Drug Development and Clinical Care

Information Science, Computer Science, Artificial Intelligence, Medicine, Medical Laboratory Science, Medical Imaging, Oncology, Life Sciences, Cell Biology, Immunology,
tumor size   precision medicine   radiomics   oncology   drug development   clinical care   multidisciplinary workshop  

In contemporary clinical oncology practice and drug development, the methods for evaluating tumor response are on the cusp of a revolution. Since the World Health Organization (WHO) proposed tumor response classification criteria for assessing the effectiveness of anti-cancer drugs in 1981, this field has undergone several improvements. Notably, th...

Clinical Validation of AI-Powered PD-L1 Tumor Proportion Score Interpretation for Predicting Immune Checkpoint Inhibitor Response in NSCLC

Information Science, Artificial Intelligence, Medicine, Medical Laboratory Science, Oncology,
Artificial Intelligence   PD-L1   Tumor Proportion Score   Non-Small Cell Lung Cancer   Immune Checkpoint Inhibitors   Clinical Validation  

Clinical Validation of AI-based Interpretation of PD-L1 Tumor Proportion Score in Predicting Response to Immune Checkpoint Inhibitors in Non-small Cell Lung Cancer In the field of tumor treatment and diagnosis, the assessment of PD-L1 (Programmed Death-Ligand 1) Tumor Proportion Score (TPS) is a critical task, especially in predicting the response ...

Towards Machine Learning-Based Quantitative Hyperspectral Image Guidance for Brain Tumor Resection

Towards Machine Learning-Based Quantitative Hyperspectral Image Guidance for Brain Tumor Resection

Information Science, Computer Science, Artificial Intelligence, Medicine, Medical Laboratory Science, Neurology, Neurosurgery, Medical Imaging,
brain tumor   hyperspectral imaging   surgical guidance   machine learning   fluorescence markers  

Study on the Role of Machine Learning-Assisted Quantitative Hyperspectral Imaging in Brain Tumor Resection Background Introduction Complete resection of malignant gliomas has always been challenged by the difficulty of distinguishing tumor cells in invasive regions. The background of this study is: In neurosurgery, the application of 5-aminolevulin...

Efficient Deep Learning-Based Automated Diagnosis from Echocardiography with Contrastive Self-Supervised Learning

Information Science, Computer Science, Artificial Intelligence, Medicine, Medical Imaging, Cardiovascular System,
deep learning   self-supervised learning   contrastive learning   echocardiography   automated diagnosis   left ventricular hypertrophy   aortic stenosis  

Breakthrough in Automated Echocardiogram Diagnosis via Deep Learning: A Comparative Study of Self-Supervised Learning Methods Research Background With the rapid development of artificial intelligence and machine learning technologies, their role in medical imaging diagnosis is becoming increasingly significant. In particular, Self-Supervised Learni...