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https://www.readbyqxmd.com/read/29777423/an-artificial-intelligent-single-cell-is-part-of-the-cell-dream-world
#1
EDITORIAL
Yiming Zeng, Xiaoyang Chen, Hongzhi Gao, Xiangdong Wang
No abstract text is available yet for this article.
May 18, 2018: Cell Biology and Toxicology
https://www.readbyqxmd.com/read/29777175/artificial-intelligence-in-radiology
#2
REVIEW
Ahmed Hosny, Chintan Parmar, John Quackenbush, Lawrence H Schwartz, Hugo J W L Aerts
Artificial intelligence (AI) algorithms, particularly deep learning, have demonstrated remarkable progress in image-recognition tasks. Methods ranging from convolutional neural networks to variational autoencoders have found myriad applications in the medical image analysis field, propelling it forward at a rapid pace. Historically, in radiology practice, trained physicians visually assessed medical images for the detection, characterization and monitoring of diseases. AI methods excel at automatically recognizing complex patterns in imaging data and providing quantitative, rather than qualitative, assessments of radiographic characteristics...
May 17, 2018: Nature Reviews. Cancer
https://www.readbyqxmd.com/read/29774921/a-flexible-pressure-sensor-based-on-rgo-polyaniline-wrapped-sponge-with-tunable-sensitivity-for-human-motion-detection
#3
Gang Ge, Yichen Cai, Qiuchun Dong, Yizhou Zhang, Jinjun Shao, Wei Huang, Xiaochen Dong
High-performance stretchable and wearable electronic skins (E-skins) with high sensitivity and a large sensing range are urgently required with the rapid development of the Internet of things and artificial intelligence. Herein, a reduced graphene oxide (rGO)/polyaniline wrapped sponge is prepared via rGO coating and the in situ synthesis of polyaniline nanowires (PANI NWs) on the backbones of sponge for the fabrication of pressure sensors. From the as-prepared flexible sensor, tunable sensitivity (0.042 to 0...
May 18, 2018: Nanoscale
https://www.readbyqxmd.com/read/29774657/cheminformatics-in-drug-discovery-an-industrial-perspective
#4
REVIEW
Hongming Chen, Thierry Kogej, Ola Engkvist
Cheminformatics has established itself as a core discipline within large scale drug discovery operations. It would be impossible to handle the amount of data generated today in a small molecule drug discovery project without persons skilled in cheminformatics. In addition, due to increased emphasis on "Big Data", machine learning and artificial intelligence, not only in the society in general, but also in drug discovery, it is expected that the cheminformatics field will be even more important in the future...
May 18, 2018: Molecular Informatics
https://www.readbyqxmd.com/read/29771674/multisource-transfer-double-dqn-based-on-actor-learning
#5
Jie Pan, Xuesong Wang, Yuhu Cheng, Qiang Yu
Deep reinforcement learning (RL) comprehensively uses the psychological mechanisms of "trial and error" and "reward and punishment" in RL as well as powerful feature expression and nonlinear mapping in deep learning. Currently, it plays an essential role in the fields of artificial intelligence and machine learning. Since an RL agent needs to constantly interact with its surroundings, the deep Q network (DQN) is inevitably faced with the need to learn numerous network parameters, which results in low learning efficiency...
June 2018: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/29771663/applications-of-deep-learning-and-reinforcement-learning-to-biological-data
#6
Mufti Mahmud, Mohammed Shamim Kaiser, Amir Hussain, Stefano Vassanelli
Rapid advances in hardware-based technologies during the past decades have opened up new possibilities for life scientists to gather multimodal data in various application domains, such as omics, bioimaging, medical imaging, and (brain/body)-machine interfaces. These have generated novel opportunities for development of dedicated data-intensive machine learning techniques. In particular, recent research in deep learning (DL), reinforcement learning (RL), and their combination (deep RL) promise to revolutionize the future of artificial intelligence...
June 2018: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/29771635/pathogenesis-based-treatments-in-primary-sjogren-s-syndrome-using-artificial-intelligence-and-advanced-machine-learning-techniques-a-systematic-literature-review
#7
Nathan Foulquier, Pascal Redou, Christophe Le Gal, Bénédicte Rouvière, Jacques-Olivier Pers, Alain Saraux
Big data analysis has become a common way to extract information from complex and large datasets among most scientific domains. This approach is now used to study large cohorts of patients in medicine. This work is a review of publications that have used artificial intelligence and advanced machine learning techniques to study physio pathogenesis-based treatments in pSS. A systematic literature review retrieved all articles reporting on the use of advanced statistical analysis applied to the study of systemic autoimmune diseases (SADs) over the last decade...
May 17, 2018: Human Vaccines & Immunotherapeutics
https://www.readbyqxmd.com/read/29770293/current-monitoring-and-innovative-predictive-modeling-to-improve-care-in-the-pediatric-cardiac-intensive-care-unit
#8
REVIEW
Mary K Olive, Gabe E Owens
The objectives of this review are (I) to describe the challenges associated with monitoring patients in the pediatric cardiac intensive care unit (PCICU) and (II) to discuss the use of innovative statistical and artificial intelligence (AI) software programs to attempt to predict significant clinical events. Patients cared for in the PCICU are clinically fragile and at risk for fatal decompensation. Current monitoring modalities are often ineffective, sometimes inaccurate, and fail to detect a deteriorating clinical status in a timely manner...
April 2018: Translational Pediatrics
https://www.readbyqxmd.com/read/29770255/a-method-for-the-interpretation-of-flow-cytometry-data-using-genetic-algorithms
#9
Cesar Angeletti
Background: Flow cytometry analysis is the method of choice for the differential diagnosis of hematologic disorders. It is typically performed by a trained hematopathologist through visual examination of bidimensional plots, making the analysis time-consuming and sometimes too subjective. Here, a pilot study applying genetic algorithms to flow cytometry data from normal and acute myeloid leukemia subjects is described. Subjects and Methods: Initially, Flow Cytometry Standard files from 316 normal and 43 acute myeloid leukemia subjects were transformed into multidimensional FITS image metafiles...
2018: Journal of Pathology Informatics
https://www.readbyqxmd.com/read/29769044/visualizing-histopathologic-deep-learning-classification-and-anomaly-detection-using-nonlinear-feature-space-dimensionality-reduction
#10
Kevin Faust, Quin Xie, Dominick Han, Kartikay Goyle, Zoya Volynskaya, Ugljesa Djuric, Phedias Diamandis
BACKGROUND: There is growing interest in utilizing artificial intelligence, and particularly deep learning, for computer vision in histopathology. While accumulating studies highlight expert-level performance of convolutional neural networks (CNNs) on focused classification tasks, most studies rely on probability distribution scores with empirically defined cutoff values based on post-hoc analysis. More generalizable tools that allow humans to visualize histology-based deep learning inferences and decision making are scarce...
May 16, 2018: BMC Bioinformatics
https://www.readbyqxmd.com/read/29765462/development-of-a-new-intelligent-joystick-for-people-with-reduced-mobility
#11
Makrem Mrabet, Yassine Rabhi, Farhat Fnaiech
Despite the diversity of electric wheelchairs, many people with physical limitations and seniors have difficulty using their standard joystick. As a result, they cannot meet their needs or ensure safe travel. Recent assistive technologies can help to give them autonomy and independence. This work deals with the real-time implementation of an artificial intelligence device to overcome these problems. Following a review of the literature from previous work, we present the methodology and process for implementing our intelligent control system on an electric wheelchair...
2018: Applied Bionics and Biomechanics
https://www.readbyqxmd.com/read/29765399/a-seasonal-time-series-model-based-on-gene-expression-programming-for-predicting-financial-distress
#12
Ching-Hsue Cheng, Chia-Pang Chan, Jun-He Yang
The issue of financial distress prediction plays an important and challenging research topic in the financial field. Currently, there have been many methods for predicting firm bankruptcy and financial crisis, including the artificial intelligence and the traditional statistical methods, and the past studies have shown that the prediction result of the artificial intelligence method is better than the traditional statistical method. Financial statements are quarterly reports; hence, the financial crisis of companies is seasonal time-series data, and the attribute data affecting the financial distress of companies is nonlinear and nonstationary time-series data with fluctuations...
2018: Computational Intelligence and Neuroscience
https://www.readbyqxmd.com/read/29763481/cutting-edge-technology-in-dermatology-virtual-reality-and-artificial-intelligence
#13
Giselle Prado, Carrie Kovarik
No abstract text is available yet for this article.
April 2018: Cutis; Cutaneous Medicine for the Practitioner
https://www.readbyqxmd.com/read/29761524/the-24th-annual-prostate-cancer-foundation-scientific-retreat-report
#14
REVIEW
Andrea K Miyahira, Howard R Soule
INTRODUCTION: The 24th Annual Prostate Cancer Foundation (PCF) Scientific Retreat was held from October 5-7, 2017, at the Omni Shoreham Hotel in Washington, DC. METHODS: The PCF Scientific Retreat is a scientific conference that specifically focuses on cutting edge research deemed to have significant promise for accelerating advances in prostate cancer biology and treatment. RESULTS: Themes highlighted at this year's meeting included: (i) new understandings in prostate cancer biology and disease progression; (ii) new mechanisms and treatment targets in advanced prostate cancer; (iii) advances in precision medicine genomics, germline genetics, and selection of targeted therapies; (iv) PSMA-targeted agents for PET imaging and radionuclide therapy; (v) approaches for improving the efficacy of immunotherapy in prostate cancer; (vi) applications of 3D Genomics in prostate cancer research; and (vii) potential applications of artificial intelligence in prostate cancer...
May 15, 2018: Prostate
https://www.readbyqxmd.com/read/29760527/prefrontal-cortex-as-a-meta-reinforcement-learning-system
#15
Jane X Wang, Zeb Kurth-Nelson, Dharshan Kumaran, Dhruva Tirumala, Hubert Soyer, Joel Z Leibo, Demis Hassabis, Matthew Botvinick
Over the past 20 years, neuroscience research on reward-based learning has converged on a canonical model, under which the neurotransmitter dopamine 'stamps in' associations between situations, actions and rewards by modulating the strength of synaptic connections between neurons. However, a growing number of recent findings have placed this standard model under strain. We now draw on recent advances in artificial intelligence to introduce a new theory of reward-based learning. Here, the dopamine system trains another part of the brain, the prefrontal cortex, to operate as its own free-standing learning system...
May 14, 2018: Nature Neuroscience
https://www.readbyqxmd.com/read/29759528/artificial-intelligence-and-the-practice-of-radiology-an-alternative-view
#16
Robert Schier
No abstract text is available yet for this article.
May 11, 2018: Journal of the American College of Radiology: JACR
https://www.readbyqxmd.com/read/29757747/the-human-touch-practical-and-ethical-implications-of-putting-ai-and-robotics-to-work-for-patients
#17
Jim Banks
We live in a time when science fiction can quickly become science fact. Within a generation, the Internet has matured from a technological marvel to a utility, and mobile telephones have redefined how we communicate. Health care, as an industry, is quick to embrace technology, so it is no surprise that the application of programmable robotic systems that can carry out actions automatically and artificial intelligence (AI), e.g., machines that learn, solve problems, and respond to their environment, is being keenly explored...
May 2018: IEEE Pulse
https://www.readbyqxmd.com/read/29756203/the-growing-role-of-machine-learning-and-artificial-intelligence-in-developmental-medicine
#18
Robert J Reynolds, Steven M Day
No abstract text is available yet for this article.
May 13, 2018: Developmental Medicine and Child Neurology
https://www.readbyqxmd.com/read/29753263/the-hirisplex-s-system-for-eye-hair-and-skin-colour-prediction-from-dna-introduction-and-forensic-developmental-validation
#19
Lakshmi Chaitanya, Krystal Breslin, Sofia Zuñiga, Laura Wirken, Ewelina Pośpiech, Magdalena Kukla-Bartoszek, Titia Sijen, Peter de Knijff, Fan Liu, Wojciech Branicki, Manfred Kayser, Susan Walsh
Forensic DNA Phenotyping (FDP), i.e. the prediction of human externally visible traits from DNA, has become a fast growing subfield within forensic genetics due to the intelligence information it can provide from DNA traces. FDP outcomes can help focus police investigations in search of unknown perpetrators, who are generally unidentifiable with standard DNA profiling. Therefore, we previously developed and forensically validated the IrisPlex DNA test system for eye colour prediction and the HIrisPlex system for combined eye and hair colour prediction from DNA traces...
April 12, 2018: Forensic Science International. Genetics
https://www.readbyqxmd.com/read/29752255/patient-centered-mobile-health-data-management-solution-for-the-german-health-care-system-the-databox-project
#20
Titus Josef Brinker, Stefanie Rudolph, Daniela Richter, Christof von Kalle
This article describes the DataBox project which offers a perspective of a new health data management solution in Germany. DataBox was initially conceptualized as a repository of individual lung cancer patient data (structured and unstructured). The patient is the owner of the data and is able to share his or her data with different stakeholders. Data is transferred, displayed, and stored online, but not archived. In the long run, the project aims at replacing the conventional method of paper- and storage-device-based handling of data for all patients in Germany, leading to better organization and availability of data which reduces duplicate diagnostic procedures, treatment errors, and enables the training as well as usage of artificial intelligence algorithms on large datasets...
May 11, 2018: JMIR Cancer
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