keyword
MENU ▼
Read by QxMD icon Read
search

Artificial intelligence prediction

keyword
https://www.readbyqxmd.com/read/29650810/-artificial-intelligence-in-drug-discovery
#1
Takeshi Fujiwara, Mayumi Kamada, Yasushi Okuno
According to the increase of data generated from analytical instruments, application of artificial intelligence(AI)technology in medical field is indispensable. In particular, practical application of AI technology is strongly required in "genomic medicine" and "genomic drug discovery" that conduct medical practice and novel drug development based on individual genomic information. In our laboratory, we have been developing a database to integrate genome data and clinical information obtained by clinical genome analysis and a computational support system for clinical interpretation of variants using AI...
April 2018: Gan to Kagaku Ryoho. Cancer & Chemotherapy
https://www.readbyqxmd.com/read/29648622/deep-learning-of-genomic-variation-and-regulatory-network-data
#2
Amalio Telenti, Christoph Lippert, Pi-Chuan Chang, Mark DePristo
The human genome is now investigated through high throughput functional assays, and through the generation of population genomic data. These advances support the identification of functional genetic variants and the prediction of traits (eg. deleterious variants and disease). This review summarizes lessons learned from the large-scale analyses of genome and exome datasets, modeling of population data and machine learning strategies to solve complex genomic sequence regions. The review also portrays the rapid adoption of artificial intelligence/deep neural networks in genomics; in particular, deep learning approaches are well suited to model the complex dependencies in the regulatory landscape of the genome, and to provide predictors for genetic variant calling and interpretation...
April 10, 2018: Human Molecular Genetics
https://www.readbyqxmd.com/read/29626659/modeling-based-optimization-approaches-for-the-development-of-anti-agrobacterium-tumefaciens-activity-using-streptomyces-sp-tn71
#3
Slim Smaoui, Karim Ennouri, Ahlem Chakchouk-Mtibaa, Imen Sellem, Kameleddine Bouchaala, Ines Karray-Rebai, Rayda Ben Ayed, Florence Mathieu, Lotfi Mellouli
A new aerobic bacterium TN71 was isolated from Tunisian Saharan soil and has been selected for its antimicrobial activity against phytopathogenic bacteria. Based on cellular morphology, physiological characterization and phylogenetic analysis, this isolate has been assigned as Streptomyces sp. TN71 strain. In an attempt to increase its anti-Agrobacterium tumefaciens activity, GYM + S (glucose, yeast extract, malt extract and starch) medium was selected out of five different production media and the medium composition was optimized...
April 4, 2018: Microbial Pathogenesis
https://www.readbyqxmd.com/read/29616480/review-on-applications-of-artificial-intelligence-methods-for-dam-and-reservoir-hydro-environment-models
#4
Mohammed Falah Allawi, Othman Jaafar, Firdaus Mohamad Hamzah, Sharifah Mastura Syed Abdullah, Ahmed El-Shafie
Efficacious operation for dam and reservoir system could guarantee not only a defenselessness policy against natural hazard but also identify rule to meet the water demand. Successful operation of dam and reservoir systems to ensure optimal use of water resources could be unattainable without accurate and reliable simulation models. According to the highly stochastic nature of hydrologic parameters, developing accurate predictive model that efficiently mimic such a complex pattern is an increasing domain of research...
April 3, 2018: Environmental Science and Pollution Research International
https://www.readbyqxmd.com/read/29610979/behavioral-modeling-for-mental-health-using-machine-learning-algorithms
#5
M Srividya, S Mohanavalli, N Bhalaji
Mental health is an indicator of emotional, psychological and social well-being of an individual. It determines how an individual thinks, feels and handle situations. Positive mental health helps one to work productively and realize their full potential. Mental health is important at every stage of life, from childhood and adolescence through adulthood. Many factors contribute to mental health problems which lead to mental illness like stress, social anxiety, depression, obsessive compulsive disorder, drug addiction, and personality disorders...
April 3, 2018: Journal of Medical Systems
https://www.readbyqxmd.com/read/29603223/assessment-of-beer-quality-based-on-a-robotic-pourer-computer-vision-and-machine-learning-algorithms-using-commercial-beers
#6
Claudia Gonzalez Viejo, Sigfredo Fuentes, Damir D Torrico, Kate Howell, Frank R Dunshea
Sensory attributes of beer are directly linked to perceived foam-related parameters and beer color. The aim of this study was to develop an objective predictive model using machine learning modeling to assess the intensity levels of sensory descriptors in beer using the physical measurements of color and foam-related parameters. A robotic pourer (RoboBEER), was used to obtain 15 color and foam-related parameters from 22 different commercial beer samples. A sensory session using quantitative descriptive analysis (QDA® ) with trained panelists was conducted to assess the intensity of 10 beer descriptors...
March 30, 2018: Journal of Food Science
https://www.readbyqxmd.com/read/29594137/artificial-intelligence-for-the-artificial-kidney-pointers-to-the-future-of-a-personalized-hemodialysis-therapy
#7
REVIEW
Miguel Hueso, Alfredo Vellido, Nuria Montero, Carlo Barbieri, Rosa Ramos, Manuel Angoso, Josep Maria Cruzado, Anders Jonsson
Background: Current dialysis devices are not able to react when unexpected changes occur during dialysis treatment or to learn about experience for therapy personalization. Furthermore, great efforts are dedicated to develop miniaturized artificial kidneys to achieve a continuous and personalized dialysis therapy, in order to improve the patient's quality of life. These innovative dialysis devices will require a real-time monitoring of equipment alarms, dialysis parameters, and patient-related data to ensure patient safety and to allow instantaneous changes of the dialysis prescription for the assessment of their adequacy...
February 2018: Kidney Diseases
https://www.readbyqxmd.com/read/29588819/an-agent-based-architecture-for-high-risk-neonate-management-at-neonatal-intensive-care-unit
#8
Jaleh Shoshtarian Malak, Reza Safdari, Hojjat Zeraati, Fatemeh Sadat Nayeri, Niloofar Mohammadzadeh, Seide Sedighe Seied Farajollah
Background: In recent years, the use of new tools and technologies has decreased the neonatal mortality rate. Despite the positive effect of using these technologies, the decisions are complex and uncertain in critical conditions when the neonate is preterm or has a low birth weight or malformations. There is a need to automate the high-risk neonate management process by creating real-time and more precise decision support tools. Objective: To create a collaborative and real-time environment to manage neonates with critical conditions at the NICU (Neonatal Intensive Care Unit) and to overcome high-risk neonate management weaknesses by applying a multi agent based analysis and design methodology as a new solution for NICU management...
January 2018: Electronic Physician
https://www.readbyqxmd.com/read/29556719/assessment-of-the-precision-id-ancestry-panel
#9
Muna Al-Asfi, Dennis McNevin, Bhavik Mehta, Daniel Power, Michelle E Gahan, Runa Daniel
AbstractThe ability to provide accurate DNA-based forensic intelligence requires analysis of multiple DNA markers to predict the biogeographical ancestry (BGA) and externally visible characteristics (EVCs) of the donor of biological evidence. Massively parallel sequencing (MPS) enables the analysis of hundreds of DNA markers in multiple samples simultaneously, increasing the value of the intelligence provided to forensic investigators while reducing the depletion of evidential material resulting from multiple analyses...
March 19, 2018: International Journal of Legal Medicine
https://www.readbyqxmd.com/read/29548875/predicting-treatment-response-to-intra-arterial-therapies-for-hepatocellular-carcinoma-with-the-use-of-supervised-machine-learning-an-artificial-intelligence-concept
#10
Aaron Abajian, Nikitha Murali, Lynn Jeanette Savic, Fabian Max Laage-Gaupp, Nariman Nezami, James S Duncan, Todd Schlachter, MingDe Lin, Jean-François Geschwind, Julius Chapiro
PURPOSE: To use magnetic resonance (MR) imaging and clinical patient data to create an artificial intelligence (AI) framework for the prediction of therapeutic outcomes of transarterial chemoembolization by applying machine learning (ML) techniques. MATERIALS AND METHODS: This study included 36 patients with hepatocellular carcinoma (HCC) treated with transarterial chemoembolization. The cohort (age 62 ± 8.9 years; 31 men; 13 white; 24 Eastern Cooperative Oncology Group performance status 0, 10 status 1, 2 status 2; 31 Child-Pugh stage A, 4 stage B, 1 stage C; 1 Barcelona Clinic Liver Cancer stage 0, 12 stage A, 10 stage B, 13 stage C; tumor size 5...
March 14, 2018: Journal of Vascular and Interventional Radiology: JVIR
https://www.readbyqxmd.com/read/29543753/artificial-intelligence-based-optimization-for-the-se-iv-removal-from-aqueous-solution-by-reduced-graphene-oxide-supported-nanoscale-zero-valent-iron-composites
#11
Rensheng Cao, Mingyi Fan, Jiwei Hu, Wenqian Ruan, Xianliang Wu, Xionghui Wei
Highly promising artificial intelligence tools, including neural network (ANN), genetic algorithm (GA) and particle swarm optimization (PSO), were applied in the present study to develop an approach for the evaluation of Se(IV) removal from aqueous solutions by reduced graphene oxide-supported nanoscale zero-valent iron (nZVI/rGO) composites. Both GA and PSO were used to optimize the parameters of ANN. The effect of operational parameters (i.e., initial pH, temperature, contact time and initial Se(IV) concentration) on the removal efficiency was examined using response surface methodology (RSM), which was also utilized to obtain a dataset for the ANN training...
March 15, 2018: Materials
https://www.readbyqxmd.com/read/29538103/harnessing-the-power-of-big-data-to-improve-graduate-medical-education-big-idea-or-bust
#12
Vineet M Arora
With the advent of electronic medical records (EMRs) fueling the rise of big data, the use of predictive analytics, machine learning, and artificial intelligence are touted as transformational tools to improve clinical care. While major investments are being made in using big data to transform health care delivery, little effort has been directed toward exploiting big data to improve graduate medical education (GME). Because our current system relies on faculty observations of competence, it is not unreasonable to ask whether big data in the form of clinical EMRs and other novel data sources can answer questions of importance in GME such as when is a resident ready for independent practice...
March 13, 2018: Academic Medicine: Journal of the Association of American Medical Colleges
https://www.readbyqxmd.com/read/29533814/prediction-of-pork-loin-quality-using-online-computer-vision-system-and-artificial-intelligence-model
#13
Xin Sun, Jennifer Young, Jeng-Hung Liu, David Newman
The objective of this project was to develop a computer vision system (CVS) for objective measurement of pork loin under industry speed requirement. Color images of pork loin samples were acquired using a CVS. Subjective color and marbling scores were determined according to the National Pork Board standards by a trained evaluator. Instrument color measurement and crude fat percentage were used as control measurements. Image features (18 color features; 1 marbling feature; 88 texture features) were extracted from whole pork loin color images...
March 7, 2018: Meat Science
https://www.readbyqxmd.com/read/29510592/production-of-low-cost-carbon-fiber-through-energy-optimization-of-stabilization-process
#14
Gelayol Golkarnarenji, Minoo Naebe, Khashayar Badii, Abbas S Milani, Reza N Jazar, Hamid Khayyam
To produce high quality and low cost carbon fiber-based composites, the optimization of the production process of carbon fiber and its properties is one of the main keys. The stabilization process is the most important step in carbon fiber production that consumes a large amount of energy and its optimization can reduce the cost to a large extent. In this study, two intelligent optimization techniques, namely Support Vector Regression (SVR) and Artificial Neural Network (ANN), were studied and compared, with a limited dataset obtained to predict physical property (density) of oxidative stabilized PAN fiber (OPF) in the second zone of a stabilization oven within a carbon fiber production line...
March 5, 2018: Materials
https://www.readbyqxmd.com/read/29510430/is-there-any-difference-in-risk-factors-between-male-and-female-patients-in-new-onset-atrial-fibrillation-after-coronary-artery-bypass-grafting
#15
Barış Akça, Nevzat Erdil, Mehmet Cengiz Colak, Olcay Murat Disli, Bektas Battaloglu, Cemil Colak
BACKGROUND:  We aimed to investigate the risk factors of post-coronary artery bypass grafting (CABG) atrial fibrillation (AF) in male and female patients without any history of AF, to identify the sex-specific risk factors, and to examine the effect of sex-specific risk factors on the overall population. METHODS:  This retrospective study was conducted using the hospital database with 4,758 patients who underwent CABG surgery. Among them, 2,836 patients with complete data participated in this study...
March 6, 2018: Thoracic and Cardiovascular Surgeon
https://www.readbyqxmd.com/read/29507784/artificial-intelligence-in-healthcare-past-present-and-future
#16
REVIEW
Fei Jiang, Yong Jiang, Hui Zhi, Yi Dong, Hao Li, Sufeng Ma, Yilong Wang, Qiang Dong, Haipeng Shen, Yongjun Wang
Artificial intelligence (AI) aims to mimic human cognitive functions. It is bringing a paradigm shift to healthcare, powered by increasing availability of healthcare data and rapid progress of analytics techniques. We survey the current status of AI applications in healthcare and discuss its future. AI can be applied to various types of healthcare data (structured and unstructured). Popular AI techniques include machine learning methods for structured data, such as the classical support vector machine and neural network, and the modern deep learning, as well as natural language processing for unstructured data...
December 2017: Stroke and Vascular Neurology
https://www.readbyqxmd.com/read/29507318/prediction-of-pka-values-for-neutral-and-basic-drugs-based-on-hybrid-artificial-intelligence-methods
#17
Mengshan Li, Huaijing Zhang, Bingsheng Chen, Yan Wu, Lixin Guan
The pKa value of drugs is an important parameter in drug design and pharmacology. In this paper, an improved particle swarm optimization (PSO) algorithm was proposed based on the population entropy diversity. In the improved algorithm, when the population entropy was higher than the set maximum threshold, the convergence strategy was adopted; when the population entropy was lower than the set minimum threshold the divergence strategy was adopted; when the population entropy was between the maximum and minimum threshold, the self-adaptive adjustment strategy was maintained...
March 5, 2018: Scientific Reports
https://www.readbyqxmd.com/read/29494914/a-review-on-experimental-design-for-pollutants-removal-in-water-treatment-with-the-aid-of-artificial-intelligence
#18
REVIEW
Mingyi Fan, Jiwei Hu, Rensheng Cao, Wenqian Ruan, Xionghui Wei
Water pollution occurs mainly due to inorganic and organic pollutants, such as nutrients, heavy metals and persistent organic pollutants. For the modeling and optimization of pollutants removal, artificial intelligence (AI) has been used as a major tool in the experimental design that can generate the optimal operational variables, since AI has recently gained a tremendous advance. The present review describes the fundamentals, advantages and limitations of AI tools. Artificial neural networks (ANNs) are the AI tools frequently adopted to predict the pollutants removal processes because of their capabilities of self-learning and self-adapting, while genetic algorithm (GA) and particle swarm optimization (PSO) are also useful AI methodologies in efficient search for the global optima...
February 20, 2018: Chemosphere
https://www.readbyqxmd.com/read/29493361/decision-support-in-diabetes-care-the-challenge-of-supporting-patients-in-their-daily-living-using-a-mobile-glucose-predictor
#19
Carmen Pérez-Gandía, Gema García-Sáez, David Subías, Agustín Rodríguez-Herrero, Enrique J Gómez, Mercedes Rigla, M Elena Hernando
BACKGROUND: In type 1 diabetes mellitus (T1DM), patients play an active role in their own care and need to have the knowledge to adapt decisions to their daily living conditions. Artificial intelligence applications can help people with type 1 diabetes in decision making and allow them to react at time scales shorter than the scheduled face-to-face visits. This work presents a decision support system (DSS), based on glucose prediction, to assist patients in a mobile environment. METHODS: The system's impact on therapeutic corrective actions has been evaluated in a randomized crossover pilot study focused on interprandial periods...
March 2018: Journal of Diabetes Science and Technology
https://www.readbyqxmd.com/read/29493285/recent-developments-of-artificial-intelligence-in-drying-of-fresh-food-a-review
#20
Qing Sun, Min Zhang, Arun S Mujumdar
Intellectualization is an important direction of drying development and artificial intelligence (AI) technologies have been widely used to solve problems of nonlinear function approximation, pattern detection, data interpretation, optimization, simulation, diagnosis, control, data sorting, clustering, and noise reduction in different food drying technologies due to the advantages of self-learning ability, adaptive ability, strong fault tolerance and high degree robustness to map the nonlinear structures of arbitrarily complex and dynamic phenomena...
March 1, 2018: Critical Reviews in Food Science and Nutrition
keyword
keyword
22554
1
2
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read
×

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"