A handheld Raman spectroscopy probe enabled detection of invasive brain cancer intraoperatively in patients with grade 2 to 4 gliomas.

The Breast Cancer Risk Assessment Tool of the National Institute (NCI) is widely used for counseling and determining eligibility breast cancer prevention trials, although its validity projecting risk in African American women uncertain. We developed a model absolute invasive compared projections with those from Tool.Data 1607 1647 control subjects Women's Contraceptive Reproductive Experiences (CARE) Study were to compute relative attributable risks that based on age at menarche, number...

Recent success in deep neural networks has generated strong interest hardware accelerators to improve speed and energy consumption. This paper presents a new type of photonic accelerator based on coherent detection that is scalable large ($N \gtrsim 10^6$) can be operated at high (GHz) speeds very low (sub-aJ) energies per multiply-and-accumulate (MAC), using the massive spatial multiplexing enabled by standard free-space optical components. In contrast previous approaches, both weights...

Advanced machine learning models are currently impossible to run on edge devices such as smart sensors and unmanned aerial vehicles owing constraints power, processing, memory. We introduce an approach inference based delocalized analog processing across networks. In this approach, named Netcast, cloud-based "smart transceivers" stream weight data devices, enabling ultraefficient photonic inference. demonstrate image recognition at ultralow optical energy of 40 attojoules per multiply (<1...

The prevalence of metabolic syndrome (obesity, glucose intolerance, low serum high-density lipoprotein cholesterol [HDL-C], high triglycerides, hypertension) is and increasing in parallel with an breast cancer incidence worldwide. HDL-C represents important aspect the syndrome, yet its role still undefined.In two population-based screening surveys during 1977-1983 1985-1987, was assayed enzymatically among 38,823 Norwegian women aged 17-54 years at entry. Height, weight, blood pressure,...

Analog optical and electronic hardware has emerged as a promising alternative to digital electronics improve the efficiency of deep neural networks (DNNs). However, previous work been limited in scalability (input vector length

Abstract As deep neural network (DNN) models grow ever-larger, they can achieve higher accuracy and solve more complex problems. This trend has been enabled by an increase in available compute power; however, efforts to continue scale electronic processors are impeded the costs of communication, thermal management, power delivery clocking. To improve scalability, we propose a digital optical (DONN) with intralayer interconnects reconfigurable input values. The path-length-independence energy...

This publication, dealing mainly with local anesthesia in dentistry, is bound to establish itself as a classic the dental literature. The book well organized, very clearly illustrated, and covers subject matter meticulous detail. There strong emphasis throughout on correlation of basic sciences clinical understanding technical performance. An excellent example lucid description specific pharmacologic actions esters amides related applications. With contributions from both medical authors,...

Brillouin light scattering offers a unique label-free approach to measure biomechanical properties non-invasively. While this technique is used in analysis of cells and tissues, its potential for visualizing structural features tissues based on the contrast has not been much exploited. Here, we present high-resolution microscopy images four basic tissue types: muscular, connective, epithelial, nervous tissues. The distinguishes between muscle fiber endomysium skeletal reveals chondrocytes...

THE OBJECTIVE of cleft palate repair is, course, not only to correct the embryonic defect but also establish normal speech. For sizeable percentage patients in whom this objective fails, various operative procedures were designed during past century residual velopharyngeal incompetence. The approach problem was based on one three objectives (Fig 1): To increase length palate; create a pad posterior nasopharyngeal wall; or barrier between oropharynx and nasal cavity. <h3>Historical...

Optical approaches to AI acceleration have gained intense interest recently due the potentially breakthrough advantages of photonics: high bandwidth, low power consumption, and efficient data movement. We overview leading photonic platforms based on beamsplitter mesh networks, weight banks, photoelectric multiplication. While theoretical performance can be orders magnitude beyond current state art, practical issues chip area, input / output, crosstalk paint a more nuanced near-term picture...

We present In-network Optical Inference (IOI), a system providing low-latency machine learning inference by leveraging programmable switches and optical matrix multiplication. IOI consists of novel transceiver module designed specifically to perform linear operations such as multiplication in the domain. IOI's transceivers are plugged into non-linear activation respond queries. demonstrate how process queries inside network, without need send cloud or edge servers, thus significantly...

Ultrahigh resolution optical coherence tomography (UHR-OCT) can image microscopic features that are not visible with the standard OCT of 5-15 µm. In previous studies, high-speed UHR-OCT has been accomplished within (VIS) and near-infrared (NIR-I) spectral ranges, specifically 550-950 nm. Here, we present a domain system operating in short-wavelength infrared (SWIR) range from 1000 to 1600 nm using supercontinuum light source an InGaAs-based spectrometer. We obtained axial 2.6 µm air, highest...

Abstract Advances in deep neural networks (DNNs) are transforming science and technology. However, the increasing computational demands of most powerful DNNs limit deployment on low-power devices, such as smartphones sensors – this trend is accelerated by simultaneous move towards Internet-of-Things (IoT) devices. Numerous efforts underway to lower power consumption, but a fundamental bottleneck remains due energy consumption matrix algebra, even for analog approaches including neuromorphic,...

We introduce an optical neural-network architecture for edge computing that takes advantage of wavelength multiplexing, high-bandwidth modulation, and integration detection.Our protocol consists a server client, which divide the task inference into two steps: (1) difficult step weight distribution, performed at (2) easy modulation detection, device.This arrangement allows large-scale neural networks to be run on low-power devices accessible by link.We perform simulations estimate speed...

Storing, processing, and learning from data is a central task in both industrial practice modern science. Recent advances statistical learning, particularly Deep Neural Networks (DNNs), have given record breaking performance on tasks game playing,^{1, 2} natural language processing,³ computer vision,⁴ computational biology,^{5, 6} many others. The rapid growth of the field has been driven by an increase amount public datasets,⁷ improvements to...

We present experimental demonstrations of ultra-low power edge computing enabled by wavelength division multiplexed optical links and time-integrating receivers. Initial experimentation show ≲ 10 fJ energy per MAC.

We use a 2D array of injection-locked VCSELs to implement spatiotemporally multiplexed optical neural network and demonstrate image classification at high accuracy with GHz line rates.

p53 genetic alterations are associated with advanced stage and aggressive tumors in a variety of human malignancies. The aim this study was to examine for evaluate the association these clinical outcome response adjuvant radiotherapy endometrioid endometrial carcinomas. mutations exons 2–11 were assessed 59 carcinomas by polymerase chain reaction–single-strand conformational polymorphism sequence analysis. Twelve (20.3%) nine polymorphisms identified. Seven codon 72 single nucleotide (SNP)...

We demonstrated a large-scale space-time-multiplexed homodyne optical neural network (ONN) using arrays of high-speed (GHz) vertical-cavity surface-emitting lasers (VCSELs). Injection locking enables precise phase control over tens VCSEL devices simultaneously, facilitating photoelectric-multiplication-based matrix operations and all-optical nonlinearity, operating at the quantum-noise limit. Our transmitters exhibit ultra-high electro-optic conversion efficiency (V_&pi;=4 mV),...

This paper analyzes the performance and energy efficiency of Netcast, a recently proposed optical neural-network architecture designed for edge computing. Netcast performs deep neural network inference by dividing computational task into two steps, which are split between (cloud) server (edge) client: (1) employs wavelength-multiplexed modulator array to encode network's weights onto an signal in analog time-wavelength basis, (2) client obtains desired matrix-vector product through...

Deep neural networks (DNNs) are reshaping the field of information processing. With their exponential growth challenging existing electronic hardware, optical (ONNs) emerging to process DNN tasks in domain with high clock rates, parallelism and low-loss data transmission. However, explore potential ONNs, it is necessary investigate full-system performance incorporating major elements, including matrix algebra nonlinear activation. Existing challenges ONNs energy consumption due low...

We propose a digital incoherent optical neural network architecture using the passive data routing and copying capabilities of optics for artificial acceleration. demonstrate proof-of-concept experiment analyze optimal use cases.

A Raman spectroscopy technique was developed and used on 8 glioblastoma patients. We demonstrate that a classification accuracy of 93% is achieved in differentiating normal brain from tumor tissue with low densities cancer cells.