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Machine Learning Program that Diagnoses Hypoadrenocorticism in Dogs Using Standard Blood Test Results

Researchers at the University of California, Davis have developed a program based on machine learning algorithms to aid in diagnosing hypoadrenocorticism.

Applying a Neural Network Algorithm to Canine Radiographs to Help Detect Left Atrial Enlargement

Researchers at the University of California, Davis have developed a method of detecting canine left atrial enlargement by applying a neural network algorithm to right lateral radiographs.

BioScript: A Programming Language for Microfluidic Devices

Prof. Philip Brisk and his colleagues from the University of California, Riverside have developed a new programming language and tool to design microfluidic (MF) devices. The new presented language, BioScript, offers a user-friendly syntax that reads user input like a cookbook recipe to optimize human readability. The advantage of the BioScript type system is that it ensures that each fluid is never consumed more than once, and that unsafe combinations of chemicals are never mixed on the chip. This result establishes the feasibility of high-level programming language and compiler design for programmable chemistry, and opens up future avenues for research in microfluidic systems. Fig 2: A Laboratory-on-a-Chip (LoC) system  

Computational Image Analysis of Guided Acoustic Waves Enables Rheological Assessment of Sub-Nanoliter Volumes

UCLA researchers in the Department of Electrical and Computer Engineering have developed an image analysis platform to measure the viscosity of nanoliter volume liquids.

IgEvolution: A Novel Tool for Clonal Analysis of Antibody Repertoires

Constructing antibody repertoires is an important error-correcting step in analyzing immunosequencing datasets that is important for reconstructing evolutionary (clonal) development of antibodies. However, the state-of-the-art repertoire construction tools typically miss low-abundance antibodies that often represent internal nodes in clonal trees and are crucially important for clonal tree reconstruction. Thus, although repertoire construction is a prerequisite for follow up clonal tree reconstruction, the existing repertoire reconstruction algorithms are not well suited for this task because they typically miss low-abundance antibodies that often represent internal nodes in clonal trees and are crucially important for clonal tree reconstruction.

Predictive Controller that Optimizes Energy and Water Used to Cool Livestock

Researchers at the University of California, Davis have developed a controller that applies environmental data to optimizing operations of livestock cooling equipment.

Low Complexity Maximum-Likelihood Decoding of Cyclic Codes

UCLA researchers in the Department of Electrical and Computer Engineering have developed a low complexity decoding algorithm of cyclic codes with better performance and lower latency than current approaches.

Method of Reducing Placebo/Nocebo Effects Associated with the Tapering of Medication and Storing Drug Tablet Fragments

UCLA researchers in the Department of Medicine have developed drug tapering schedule software to reduce factors that may impede patients’ discontinuation of a drug.

Deep Learning of Biomimetic Sensorimotor Control for Biomechanical Human Animation

UCLA researchers from the Department of Computer Science have developed a computer simulation model and associated software system for biomimetic human sensorimotor control.

Software for Automated Microfluidic Chip Design

Professor Brisk’s research group at the University of California, Riverside, has developed software to design and analyze an entire microfluidic chip. This is done using Microfluidic Design Automation (MDA) software to synthesize and physically lay out the devices.This software uses Microfluidic  Design  Automation (MDA) to  physically  render chips.  This  approach  is  similar  to  Electronic  Design Automation (EDA) in the semiconductor industry. The  software  automatically creates a chip architecture that is converted to MHDL, a  human-readable microfluidic hardware design language, enabling manual refinement. When  the  chip  designer  is  satisfied  with  the  architecture,  the software  physically  lays  out  the  different  layers  of  the  chip. The  output  is  an  AutoCAD  DXF  (or  other  vector  graphics) file that can be transferred to a foundry for fabrication. Fig. 1 shows a microfluidic device layout designed and laid-out by the UCR software.  

Use of Machine Learning to Predict Non-Diagnostic Home Sleep Apnea Tests

Researchers led by Robert Stretch from the Division of Pulmonary, Critical Care & Sleep Medicine at UCLA have developed an algorithm that can predict whether a patient will have a non-diagnostic home sleep apnea test based upon data from the electronic health record and a brief questionnaire.

Automatic Identification of Ophthalmic Medication for The Visually Impaired

Researchers at UCI are developing technology that allows visually impaired patients to use their smartphones to take pictures of their eye medication/eye drop bottles. The technology will recognize the eye medication and verbally communicate the medication and will audibly confirm the medication along with the instructions on use.

Fast Deep Neural Network (DNN) Training/Execution on Hardware Platforms

With the growing range of applications for Deep Neural Networks (DNNs), the demand for higher accuracy has directly impacted the depth of the state-of-the-art models. Although deeper networks are shown to have higher accuracy, they suffer from drastically long training time and slow convergence speed with high computational complexity.

New Classes Of Cage And Polyhedron And New Classes Of Nanotube And Nanotube With Planar Faces

UCLA researchers have developed a novel algorithm that can be used to design unique self-assembled molecules and nanostructures.

Healthcare Hand Hygiene Medical Training Software

UCI researchers have developed a curriculum for training and evaluation of customers performing Healthcare Hand Hygiene.

Advanced Airway Management: Intubation medical Training Software

UCI researchers have developed a curriculum for training and evaluation of customers performing Advanced Airway Mangement: Intubation.

Method and Apparatus for Movement Therapy Gaming System

Rehabilitation therapy, while an important tool for the long term recovery of patients affected by brain injury or disease, is expensive and requires one-on-one attention from a certified healthcare professional. UCI researchers have developed a computer-based system that provides arm movement therapy for patients. The system allows patients to independently practice hand and arm movements, improving therapeutic outcomes, while reducing hospital visits and cost for both patients and healthcare providers.

Financial Model for Informing Value-Based Payment Decisions

Researchers led by David Johnson from the Department of Urologic Oncology and the West Los Angeles Veteran’s Affairs Medical Center have developed an interactive web platform that predicts the financial outcomes for various stakeholders (physicians, hospitals, and payers) of transitioning from fee-for-service to bundled payments for robotic radical prostatectomy.

Head Related Impulse Response Interpolation, Extrapolation and Personalization Using Deep Belief Networks

In machine learning, a deep belief network is a generative graphical model, or alternatively a class of deep neural network, composed of multiple layers of latent variables, with connections between the layers but not between units within each layer.

System And Method For Binaural Spatial Processing Of Audio Signals

Audio signal processing is the intentional modification of sound signals to create an auditory effect for a listener to alter the perception of the temporal, spatial, pitch and/or volume aspects of the received sound. Audio signal processing can be performed in analog and/or digital domains by audio signal processing systems. For example, analog processing techniques can use circuitry to modify the electrical signals associated with the sound, whereas digital processing techniques can include algorithms to modify the digital representation, e.g., binary code, corresponding to the electrical signals associated with the sound.  Binaural sound recordings are produced by a stereo recording of two microphones inside the ears of a human or a mannequin head. Such recordings include most cues for sound spatialization detected by humans, and thus, they are able to realistically transmit the localization of the recorded sounds, and in effect provide a three dimensional experience of the soundscape for the listener.

AI Enabled UAV Route-Planning Algorithm with Applications to Search and Surveillance

Portable UAVs such as quad-copters have made huge inroads in the last several years in various fields of aerial photography and surveillance. Drones can efficiently and cheaply hover over/follow a target of interest and capture unique perspectives of wildlife, real-estate, sporting events and operational environments such as law enforcement or military. More challenging however is the application of UAVs for large area search and surveillance. In these scenarios, a search pattern must be established which can cover many square miles and is far too expansive for a UAVs typical battery to sustain. To make UAVs more broadly effective in large area search and target identification, new path planning algorithms are needed to efficiently eliminate areas of low probability while focusing on search areas most likely to contain the subject of interest. Likewise, improved image classifiers are needed to aid in separating targets of interest from background terrain, thus expediting the search within given battery limitations

Cloud- enabled Wireless pH Monitoring in Laboratory Sample Vials

A team of inventors at UCI have developed a miniaturized, wireless pH sensing system capable of monitoring the pH of laboratory samples in real-time with cloud-enabled connections for data collection. The sensor is designed to fit into the caps of standard sample vials, providing continuous measurements and eliminating the need to open vials during sensing.

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