Please wait. Data is being processed...

News of Inventions: 345673
Files of Inventions: 220
Groups of Inventors: 50

Friend Requests:
Private Messages:

Today's News: 28
Yesterday's News: 107

Today: 11 April 2021, Sunday.

Links

All latest news of Inventions in one place

Listed news of Inventions: 27 from total 345673

Analytics

Filters

Welcome, Guest

News for Artificial intelligence

#1

View it

Name	AI Is Not Actually an Existential Threat to Humanity, Scientists Say
Description	We encounter artificial intelligence (AI) every day. AI describes computer systems that are able to perform tasks that normally require human intelligence. When you search something on the internet, the top results you see are decided by AI. #Artificial intelligence
Field	# Artificial intelligence
Updated	11 April 2021

#2

View it

Name	Artificial neural network model for predicting changes in ion channel conductance based on cardiac action potential shapes generated via simulation \| Scientific Reports
Description	Many studies have revealed changes in specific protein channels due to physiological causes such as mutation and their effects on action potential duration changes. However, no studies have been conducted to predict the type of protein channel abnormalities that occur through an action potential (AP) shape. Therefore, in this study, we aim to predict the ion channel conductance that is altered from various AP shapes using a machine learning algorithm. We perform electrophysiological simulations using a single-cell model to obtain AP shapes based on variations in the ion channel conductance. In the AP simulation, we increase and decrease the conductance of each ion channel at a constant rate, resulting in 1,980 AP shapes and one standard AP shape without any changes in the ion channel conductance. Subsequently, we calculate the AP difference shapes between them and use them as the input of the machine learning model to predict the changed ion channel conductance. In this study, we demonstrate that the changed ion channel conductance can be predicted with high prediction accuracy, as reflected by an F1 score of 0.985, using only AP shapes and simple machine learning. #Artificial intelligence
Field	# Artificial intelligence
Updated	09 April 2021

#3

View it

Name	Quantitative salivary gland SPECT/CT using deep convolutional neural networks \| Scientific Reports
Description	Quantitative single-photon emission computed tomography/computed tomography (SPECT/CT) using Tc-99m pertechnetate aids in evaluating salivary gland function. However, gland segmentation and quantitation of gland uptake is challenging. We develop a salivary gland SPECT/CT with automated segmentation using a deep convolutional neural network (CNN). The protocol comprises SPECT/CT at 20 min, sialagogue stimulation, and SPECT at 40 min post-injection of Tc-99m pertechnetate (555 MBq). The 40-min SPECT was reconstructed using the 20-min CT after misregistration correction. Manual salivary gland segmentation for %injected dose (%ID) by human experts proved highly reproducible, but took 15 min per scan. An automatic salivary segmentation method was developed using a modified 3D U-Net for end-to-end learning from the human experts (n = 333). The automatic segmentation performed comparably with human experts in voxel-wise comparison (mean Dice similarity coefficient of 0.81 for parotid and 0.79 for submandibular, respectively) and gland %ID correlation (R2 = 0.93 parotid, R2 = 0.95 submandibular) with an operating time less than 1 min. The algorithm generated results that were comparable to the reference data. In conclusion, with the aid of a CNN, we developed a quantitative salivary gland SPECT/CT protocol feasible for clinical applications. The method saves analysis time and manual effort while reducing patients’ radiation exposure. #Artificial intelligence
Field	# Artificial intelligence
Updated	09 April 2021

#4

View it

Name	New machine learning method accurately predicts battery state of health
Description	Electrical batteries are increasingly crucial in a variety of applications, from integration of intermittent energy sources with demand, to unlocking carbon-free power for the transportation sector through electric vehicles ... #Artificial Intelligence
Field	# Artificial Intelligence
Updated	09 April 2021

#5

View it

Name	In an AI world we need to teach students how to work with robot writers
Description	Robots are writing more of what we read on the internet. And artificial intelligence (AI) writing tools are becoming freely available for anyone, including students, to use. #Artificial intelligence
Field	# Artificial intelligence
Updated	09 April 2021

#6

View it

Name	Lost painting found HIDDEN beneath famous Picasso portrait using AI X-ray scanner after 120 years
Description	ARTIFICIAL intelligence has brought to life a hidden painting beneath a Picasso masterpiece.Pablo Picasso's 'The Crouching Beggar' was created in 1902 #Artificial intelligence
Field	# Artificial intelligence
Updated	09 April 2021

#7

View it

Name	Mi AI Smart Speaker (Second Generation) With 8W Output, Voice Recognition Launched by Xiaomi \| Technology News
Description	Mi AI Smart Speaker (second generation) has debuted in China and offers an 8W output with its 2-inch speakers. The Mi AI Smart Speaker is priced at CNY 199 (roughly Rs. 2,300) and it is unclear if Xiaomi will launch it in India. #Artificial intelligence
Field	# Artificial intelligence
Updated	09 April 2021

#8

View it

Name	Ability of artificial intelligence to detect T1 esophageal squamous cell carcinoma from endoscopic videos and the effects of real-time assistance \| Scientific Reports
Description	Diagnosis using artificial intelligence (AI) with deep learning could be useful in endoscopic examinations. We investigated the ability of AI to detect superficial esophageal squamous cell carcinoma (ESCC) from esophagogastroduodenoscopy (EGD) videos. We retrospectively collected 8428 EGD images of esophageal cancer to develop a convolutional neural network through deep learning. We evaluated the detection accuracy of the AI diagnosing system compared with that of 18 endoscopists. We used 144 EGD videos for the two validation sets. First, we used 64 EGD observation videos of ESCCs using both white light imaging (WLI) and narrow-band imaging (NBI). We then evaluated the system using 80 EGD videos from 40 patients (20 with superficial ESCC and 20 with non-ESCC). In the first set, the AI system correctly diagnosed 100% ESCCs. In the second set, it correctly detected 85% (17/20) ESCCs. Of these, 75% (15/20) and 55% (11/22) were detected by WLI and NBI, respectively, and the positive predictive value was 36.7%. The endoscopists correctly detected 45% (25–70%) ESCCs. With AI real-time assistance, the sensitivities of the endoscopists were significantly improved without AI assistance (p < 0.05). AI can detect superficial ESCCs from EGD videos with high sensitivity and the sensitivity of the endoscopist was improved with AI real-time support. #Artificial Intelligence
Field	# Artificial Intelligence
Updated	08 April 2021

#9

View it

Name	A deep learning approach to identifying immunogold particles in electron microscopy images \| Scientific Reports
Description	Electron microscopy (EM) enables high-resolution visualization of protein distributions in biological tissues. For detection, gold nanoparticles are typically used as an electron-dense marker for immunohistochemically labeled proteins. Manual annotation of gold particle labels is laborious and time consuming, as gold particle counts can exceed 100,000 across hundreds of image segments to obtain conclusive data sets. To automate this process, we developed Gold Digger, a software tool that uses a modified pix2pix deep learning network capable of detecting and annotating colloidal gold particles in biological EM images obtained from both freeze-fracture replicas and plastic sections prepared with the post-embedding method. Gold Digger performs at near-human-level accuracy, can handle large images, and includes a user-friendly tool with a graphical interface for proof reading outputs by users. Manual error correction also helps for continued re-training of the network to improve annotation accuracy over time. Gold Digger thus enables rapid high-throughput analysis of immunogold-labeled EM data and is freely available to the research community. #Artificial Intelligence
Field	# Artificial Intelligence
Updated	08 April 2021

#10

View it

Name	Google AI scientist: Google’s senior AI scientist resigns after colleagues' firing, reveals email
Description	Though at least two Google engineers had earlier resigned to protest the dismissal of artificial intelligence (AI) researcher Timnit Gebru, Bengio is the highest-profile employee yet to depart. #Artificial intelligence
Field	# Artificial intelligence
Updated	07 April 2021

#11

View it

Name	Am I arguing with a machine? AI debaters highlight need for transparency
Description	TBD #Artificial intelligence
Field	# Artificial intelligence
Updated	07 April 2021

#12

View it

Name	An artificial intelligence tool that can help detect melanoma
Description	Melanoma is a type of malignant tumor responsible for more than 70 percent of all skin cancer-related deaths worldwide. For years, physicians have relied on visual inspection to identify suspicious pigmented lesions (SPLs), ... #Artificial Intelligence
Field	# Artificial Intelligence
Updated	07 April 2021

#13

View it

Name	Evaluating eligibility criteria of oncology trials using real-world data and AI \| Nature
Description	TBD #Artificial intelligence
Field	# Artificial intelligence
Updated	07 April 2021

#14

View it

Name	AI uses patient data to optimize selection of eligibility criteria for clinical trials
Description	TBD #Artificial intelligence
Field	# Artificial intelligence
Updated	07 April 2021

#15

View it

Name	Hybrid neural network based on novel audio feature for vehicle type identification \| Scientific Reports
Description	Due to the audio information of different types of vehicle models are distinct, the vehicle information can be identified by the audio signal of vehicle accurately. In real life, in order to determine the type of vehicle, we do not need to obtain the visual information of vehicles and just need to obtain the audio information. In this paper, we extract and stitching different features from different aspects: Mel frequency cepstrum coefficients in perceptual characteristics, pitch class profile in psychoacoustic characteristics and short-term energy in acoustic characteristics. In addition, we improve the neural networks classifier by fusing the LSTM unit into the convolutional neural networks. At last, we put the novel feature to the hybrid neural networks to recognize different vehicles. The results suggest the novel feature we proposed in this paper can increase the recognition rate by 7%; destroying the training data randomly by superimposing different kinds of noise can improve the anti-noise ability in our identification system; and LSTM has great advantages in modeling time series, adding LSTM to the networks can improve the recognition rate of 3.39%. #Artificial intelligence
Field	# Artificial intelligence
Updated	07 April 2021

#16

View it

Name	LG Electronics: After quitting smartphones, LG to now focus on vehicle parts, AI - Latest News \| Gadgets Now
Description	Leaving its ill-fated mobile business behind, LG Electronics will zero in on bolstering promising sectors, like vehicle components, connected devices and artificial intelligence (AI), industry observers said on Monday, hoping that the segments will fill the hole left by its money-losing unit. #Artificial intelligence
Field	# Artificial intelligence
Updated	06 April 2021

#17

View it

Name	Seeking the cellular mechanisms of disease, with help from machine learning \| MIT News \| Massachusetts Institute of Technology
Description	MIT Associate Professor Caroline Uhler uses machine learning to better understand gene regulation, health, and disease. She works to integrate different types of data, like genome sequencing, imaging, and the 3D packing of the DNA. #Artificial Intelligence
Field	# Artificial Intelligence
Updated	06 April 2021

#18

View it

Name	New artificial neural network design can differentiate between healthy and diseased skin
Description	The founding chair of the Biomedical Engineering Department at the University of Houston is reporting a new deep neural network architecture that provides early diagnosis of systemic sclerosis (SSc), a rare autoimmune disease ... #Artificial intelligence
Field	# Artificial intelligence
Updated	06 April 2021

#19

View it

Name	Time to regulate AI that interprets human emotions
Description	TBD #Artificial intelligence
Field	# Artificial intelligence
Updated	06 April 2021

#20

View it

Name	New machine learning tool converts 2D material images into 3D structures
Description	A new algorithm developed at Imperial College London can convert 2D images of composite materials into 3D structures. #Artificial Intelligence
Field	# Artificial Intelligence
Updated	06 April 2021

#21

View it

Name	Top 20 Data Science And Machine Learning Platforms: Gartner
Description	Gartner’s Magic Quadrant for data science and machine learning platform 2021 includes AWS, Google, Microsoft, IBM, SAS MathWorks, Databricks, Alteryx and H2O.ai. #Artificial Intelligence
Field	# Artificial Intelligence
Updated	06 April 2021

#22

View it

Name	Google AI scientist resigns after controversial ousting of colleagues - CNET
Description	Samy Bengio is the highest ranking Google employee to leave the company as its AI division has been thrown into turmoil. #Artificial intelligence
Field	# Artificial intelligence
Updated	06 April 2021

#23

View it

Name	Prediction of PCR amplification from primer and template sequences using recurrent neural network \| Scientific Reports
Description	We have developed a novel method to predict the success of PCR amplification for a specific primer set and DNA template based on the relationship between the primer sequence and the template. To perform the prediction using a recurrent neural network, the usual double-stranded formation between the primer and template nucleotide sequences was herein expressed as a five-lettered word. The set of words (pseudo-sentences) was placed to indicate the success or failure of PCR targeted to learn recurrent neural network (RNN). After learning pseudo-sentences, RNN predicted PCR results from pseudo-sentences which were created by primer and template sequences with 70% accuracy. These results suggest that PCR results could be predicted using learned RNN and the trained RNN could be used as a replacement for preliminary PCR experimentation. This is the first report which utilized the application of neural network for primer design and prediction of PCR results. #Artificial intelligence
Field	# Artificial intelligence
Updated	05 April 2021

#24

View it

Name	How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals \| Nature Medicine
Description	A comprehensive overview of medical AI devices approved by the US Food and Drug Administration sheds new light on limitations of the evaluation process that can mask vulnerabilities of devices when they are deployed on patients. #Artificial intelligence
Field	# Artificial intelligence
Updated	05 April 2021

#25

View it

Name	Towards increasing the clinical applicability of machine learning biomarkers in psychiatry \| Nature Human Behaviour
Description	#Artificial Intelligence
Field	# Artificial Intelligence
Updated	05 April 2021

#26

View it

Name	Reply to: Towards increasing the clinical applicability of machine learning biomarkers in psychiatry \| Nature Human Behaviour
Description	#Artificial Intelligence
Field	# Artificial Intelligence
Updated	05 April 2021

#27

View it

Name	Faster Fusion Reactor Calculations Thanks to AI
Description	TBD #Artificial intelligence
Field	# Artificial intelligence
Updated	04 April 2021

Basic

Home
Up

What we are

Inventions

Analytics

Counters

Join us

Contact Us

The goal of nerds-net.com is to support collaboration of Innovators and to promote Innovations globally

Copyright © Nerds Network, 2016. All Rights Reserved