journal
MENU ▼
Read by QxMD icon Read
search

Artificial Intelligence in Medicine

journal
https://www.readbyqxmd.com/read/29310966/improving-the-anesthetic-process-by-a-fuzzy-rule-based-medical-decision-system
#1
Juan Albino Mendez, Ana Leon, Ayoze Marrero, Jose M Gonzalez-Cava, Jose Antonio Reboso, Jose Ignacio Estevez, José F Gomez-Gonzalez
OBJECTIVE: The main objective of this research is the design and implementation of a new fuzzy logic tool for automatic drug delivery in patients undergoing general anesthesia. The aim is to adjust the drug dose to the real patient needs using heuristic knowledge provided by clinicians. A two-level computer decision system is proposed. The idea is to release the clinician from routine tasks so that he can focus on other variables of the patient. METHODS: The controller uses the Bispectral Index (BIS) to assess the hypnotic state of the patient...
January 5, 2018: Artificial Intelligence in Medicine
https://www.readbyqxmd.com/read/29306539/random-ensemble-learning-for-eeg-classification
#2
Mohammad-Parsa Hosseini, Dario Pompili, Kost Elisevich, Hamid Soltanian-Zadeh
Real-time detection of seizure activity in epilepsy patients is critical in averting seizure activity and improving patients' quality of life. Accurate evaluation, presurgical assessment, seizure prevention, and emergency alerts all depend on the rapid detection of seizure onset. A new method of feature selection and classification for rapid and precise seizure detection is discussed wherein informative components of electroencephalogram (EEG)-derived data are extracted and an automatic method is presented using infinite independent component analysis (I-ICA) to select independent features...
January 3, 2018: Artificial Intelligence in Medicine
https://www.readbyqxmd.com/read/29275896/bayesian-averaging-over-decision-tree-models-for-trauma-severity-scoring
#3
V Schetinin, L Jakaite, W Krzanowski
Health care practitioners analyse possible risks of misleading decisions and need to estimate and quantify uncertainty in predictions. We have examined the "gold" standard of screening a patient's conditions for predicting survival probability, based on logistic regression modelling, which is used in trauma care for clinical purposes and quality audit. This methodology is based on theoretical assumptions about data and uncertainties. Models induced within such an approach have exposed a number of problems, providing unexplained fluctuation of predicted survival and low accuracy of estimating uncertainty intervals within which predictions are made...
December 21, 2017: Artificial Intelligence in Medicine
https://www.readbyqxmd.com/read/29241659/a-novel-method-for-predicting-kidney-stone-type-using-ensemble-learning
#4
Yassaman Kazemi, Seyed Abolghasem Mirroshandel
The high morbidity rate associated with kidney stone disease, which is a silent killer, is one of the main concerns in healthcare systems all over the world. Advanced data mining techniques such as classification can help in the early prediction of this disease and reduce its incidence and associated costs. The objective of the present study is to derive a model for the early detection of the type of kidney stone and the most influential parameters with the aim of providing a decision-support system. Information was collected from 936 patients with nephrolithiasis at the kidney center of the Razi Hospital in Rasht from 2012 through 2016...
December 11, 2017: Artificial Intelligence in Medicine
https://www.readbyqxmd.com/read/29241658/spatiotemporal-bayesian-networks-for-malaria-prediction
#5
Peter Haddawy, A H M Imrul Hasan, Rangwan Kasantikul, Saranath Lawpoolsri, Patiwat Sa-Angchai, Jaranit Kaewkungwal, Pratap Singhasivanon
Targeted intervention and resource allocation are essential for effective malaria control, particularly in remote areas, with predictive models providing important information for decision making. While a diversity of modeling technique have been used to create predictive models of malaria, no work has made use of Bayesian networks. Bayes nets are attractive due to their ability to represent uncertainty, model time lagged and nonlinear relations, and provide explanations. This paper explores the use of Bayesian networks to model malaria, demonstrating the approach by creating village level models with weekly temporal resolution for Tha Song Yang district in northern Thailand...
December 11, 2017: Artificial Intelligence in Medicine
https://www.readbyqxmd.com/read/29208328/different-approaches-for-identifying-important-concepts-in-probabilistic-biomedical-text-summarization
#6
Milad Moradi, Nasser Ghadiri
Automatic text summarization tools help users in the biomedical domain to acquire their intended information from various textual resources more efficiently. Some of biomedical text summarization systems put the basis of their sentence selection approach on the frequency of concepts extracted from the input text. However, it seems that exploring other measures rather than the raw frequency for identifying valuable contents within an input document, or considering correlations existing between concepts, may be more useful for this type of summarization...
December 2, 2017: Artificial Intelligence in Medicine
https://www.readbyqxmd.com/read/29183738/isgpt-an-optimized-model-to-identify-sub-golgi-protein-types-using-svm-and-random-forest-based-feature-selection
#7
M Saifur Rahman, Md Khaledur Rahman, M Kaykobad, M Sohel Rahman
The Golgi Apparatus (GA) is a key organelle for protein synthesis within the eukaryotic cell. The main task of GA is to modify and sort proteins for transport throughout the cell. Proteins permeate through the GA on the ER (Endoplasmic Reticulum) facing side (cis side) and depart on the other side (trans side). Based on this phenomenon, we get two types of GA proteins, namely, cis-Golgi protein and trans-Golgi protein. Any dysfunction of GA proteins can result in congenital glycosylation disorders and some other forms of difficulties that may lead to neurodegenerative and inherited diseases like diabetes, cancer and cystic fibrosis...
November 25, 2017: Artificial Intelligence in Medicine
https://www.readbyqxmd.com/read/29169647/an-eeg-based-functional-connectivity-measure-for-automatic-detection-of-alcohol-use-disorder
#8
Wajid Mumtaz, Mohamad Naufal B Mohamad Saad, Nidal Kamel, Syed Saad Azhar Ali, Aamir Saeed Malik
BACKGROUND: The abnormal alcohol consumption could cause toxicity and could alter the human brain's structure and function, termed as alcohol used disorder (AUD). Unfortunately, the conventional screening methods for AUD patients are subjective and manual. Hence, to perform automatic screening of AUD patients, objective methods are needed. The electroencephalographic (EEG) data have been utilized to study the differences of brain signals between alcoholics and healthy controls that could further developed as an automatic screening tool for alcoholics...
November 20, 2017: Artificial Intelligence in Medicine
https://www.readbyqxmd.com/read/29169646/development-of-an-intelligent-surgical-training-system-for-thoracentesis
#9
Hirenkumar Nakawala, Giancarlo Ferrigno, Elena De Momi
Surgical training improves patient care, helps to reduce surgical risks, increases surgeon's confidence, and thus enhances overall patient safety. Current surgical training systems are more focused on developing technical skills, e.g. dexterity, of the surgeons while lacking the aspects of context-awareness and intra-operative real-time guidance. Context-aware intelligent training systems interpret the current surgical situation and help surgeons to train on surgical tasks. As a prototypical scenario, we chose Thoracentesis procedure in this work...
November 20, 2017: Artificial Intelligence in Medicine
https://www.readbyqxmd.com/read/29129481/image-processing-strategies-based-on-saliency-segmentation-for-object-recognition-under-simulated-prosthetic-vision
#10
Heng Li, Xiaofan Su, Jing Wang, Han Kan, Tingting Han, Yajie Zeng, Xinyu Chai
BACKGROUND AND OBJECTIVE: Current retinal prostheses can only generate low-resolution visual percepts constituted of limited phosphenes which are elicited by an electrode array and with uncontrollable color and restricted grayscale. Under this visual perception, prosthetic recipients can just complete some simple visual tasks, but more complex tasks like face identification/object recognition are extremely difficult. Therefore, it is necessary to investigate and apply image processing strategies for optimizing the visual perception of the recipients...
November 9, 2017: Artificial Intelligence in Medicine
https://www.readbyqxmd.com/read/29111222/ssel-ade-a-semi-supervised-ensemble-learning-framework-for-extracting-adverse-drug-events-from-social-media
#11
Jing Liu, Songzheng Zhao, Gang Wang
With the development of Web 2.0 technology, social media websites have become lucrative but under-explored data sources for extracting adverse drug events (ADEs), which is a serious health problem. Besides ADE, other semantic relation types (e.g., drug indication and beneficial effect) could hold between the drug and adverse event mentions, making ADE relation extraction - distinguishing ADE relationship from other relation types - necessary. However, conducting ADE relation extraction in social media environment is not a trivial task because of the expertise-dependent, time-consuming and costly annotation process, and the feature space's high-dimensionality attributed to intrinsic characteristics of social media data...
October 27, 2017: Artificial Intelligence in Medicine
https://www.readbyqxmd.com/read/29054572/chaotic-genetic-algorithm-and-adaboost-ensemble-metamodeling-approach-for-optimum-resource-planning-in-emergency-departments
#12
Milad Yousefi, Moslem Yousefi, Ricardo Poley Martins Ferreira, Joong Hoon Kim, Flavio S Fogliatto
Long length of stay and overcrowding in emergency departments (EDs) are two common problems in the healthcare industry. To decrease the average length of stay (ALOS) and tackle overcrowding, numerous resources, including the number of doctors, nurses and receptionists need to be adjusted, while a number of constraints are to be considered at the same time. In this study, an efficient method based on agent-based simulation, machine learning and the genetic algorithm (GA) is presented to determine optimum resource allocation in emergency departments...
October 17, 2017: Artificial Intelligence in Medicine
https://www.readbyqxmd.com/read/29042162/pronation-and-supination-analysis-based-on-biomechanical-signals-from-parkinson-s-disease-patients
#13
Alejandro Garza-Rodríguez, Luis Pastor Sánchez-Fernández, Luis Alejandro Sánchez-Pérez, Christopher Ornelas-Vences, Mariane Ehrenberg-Inzunza
In this work, a fuzzy inference model to evaluate hands pronation/supination exercises during the MDS-UPDRS motor examination is proposed to analyze different extracted features from the bio-mechanical signals acquired from patients with Parkinson's disease (PD) in different stages of severity. Expert examiners perform visual assessments to evaluate several aspects of the disease. Some previous work on this subject does not contemplate the MDS-UPDRS guidelines. The method proposed in this work quantifies the biomechanical features examiners evaluate...
October 14, 2017: Artificial Intelligence in Medicine
https://www.readbyqxmd.com/read/28993124/learning-ensemble-classifiers-for-diabetic-retinopathy-assessment
#14
Emran Saleh, Jerzy Błaszczyński, Antonio Moreno, Aida Valls, Pedro Romero-Aroca, Sofia de la Riva-Fernández, Roman Słowiński
Diabetic retinopathy is one of the most common comorbidities of diabetes. Unfortunately, the recommended annual screening of the eye fundus of diabetic patients is too resource-consuming. Therefore, it is necessary to develop tools that may help doctors to determine the risk of each patient to attain this condition, so that patients with a low risk may be screened less frequently and the use of resources can be improved. This paper explores the use of two kinds of ensemble classifiers learned from data: fuzzy random forest and dominance-based rough set balanced rule ensemble...
October 6, 2017: Artificial Intelligence in Medicine
https://www.readbyqxmd.com/read/28986108/temporal-case-based-reasoning-for-type-1-diabetes-mellitus-bolus-insulin-decision-support
#15
Daniel Brown, Arantza Aldea, Rachel Harrison, Clare Martin, Ian Bayley
Individuals with type 1 diabetes have to monitor their blood glucose levels, determine the quantity of insulin required to achieve optimal glycaemic control and administer it themselves subcutaneously, multiple times per day. To help with this process bolus calculators have been developed that suggest the appropriate dose. However these calculators do not automatically adapt to the specific circumstances of an individual and require fine-tuning of parameters, a process that often requires the input of an expert...
October 3, 2017: Artificial Intelligence in Medicine
https://www.readbyqxmd.com/read/28958803/evaluation-of-an-automated-knowledge-based-textual-summarization-system-for-longitudinal-clinical-data-in-the-intensive-care-domain
#16
Ayelet Goldstein, Yuval Shahar, Efrat Orenbuch, Matan J Cohen
OBJECTIVES: To examine the feasibility of the automated creation of meaningful free-text summaries of longitudinal clinical records, using a new general methodology that we had recently developed; and to assess the potential benefits to the clinical decision-making process of using such a method to generate draft letters that can be further manually enhanced by clinicians. METHODS: We had previously developed a system, CliniText (CTXT), for automated summarization in free text of longitudinal medical records, using a clinical knowledge base...
October 2017: Artificial Intelligence in Medicine
https://www.readbyqxmd.com/read/28943333/finding-discriminative-and-interpretable-patterns-in-sequences-of-surgical-activities
#17
Germain Forestier, François Petitjean, Pavel Senin, Laurent Riffaud, Pierre-Louis Henaux, Pierre Jannin
OBJECTIVE: Surgery is one of the riskiest and most important medical acts that is performed today. Understanding the ways in which surgeries are similar or different from each other is of major interest to understand and analyze surgical behaviors. This article addresses the issue of identifying discriminative patterns of surgical practice from recordings of surgeries. These recordings are sequences of low-level surgical activities representing the actions performed by surgeons during surgeries...
October 2017: Artificial Intelligence in Medicine
https://www.readbyqxmd.com/read/28939302/a-hierarchical-classifier-based-on-human-blood-plasma-fluorescence-for-non-invasive-colorectal-cancer-screening
#18
Felipe Soares, Karin Becker, Michel J Anzanello
Colorectal cancer (CRC) a leading cause of death by cancer, and screening programs for its early identification are at the heart of the increasing survival rates. To motivate population participation, non-invasive, accurate, scalable and cost-effective diagnosis methods are required. Blood fluorescence spectroscopy provides rich information that can be used for cancer identification. The main challenges in analyzing blood fluorescence data for CRC classification are related to its high dimensionality and inherent variability, especially when analyzing a small number of samples...
October 2017: Artificial Intelligence in Medicine
https://www.readbyqxmd.com/read/28911905/gaussian-process-classification-of-superparamagnetic-relaxometry-data-phantom-study
#19
Javad Sovizi, Kelsey B Mathieu, Sara L Thrower, Wolfgang Stefan, John D Hazle, David Fuentes
MOTIVATION: Superparamagnetic relaxometry (SPMR) is an emerging technology that holds potential for use in early cancer detection. Measurement of the magnetic field after the excitation of cancer-bound superparamagnetic iron oxide nanoparticles (SPIONs) enables the reconstruction of SPIONs spatial distribution and hence tumor detection. However, image reconstruction often requires solving an ill-posed inverse problem that is computationally challenging and sensitive to measurement uncertainty...
October 2017: Artificial Intelligence in Medicine
https://www.readbyqxmd.com/read/28882544/gene2disco-gene-to-disease-using-disease-commonalities
#20
Marco Frasca
OBJECTIVE: Finding the human genes co-causing complex diseases, also known as "disease-genes", is one of the emerging and challenging tasks in biomedicine. This process, termed gene prioritization (GP), is characterized by a scarcity of known disease-genes for most diseases, and by a vast amount of heterogeneous data, usually encoded into networks describing different types of functional relationships between genes. In addition, different diseases may share common profiles (e.g. genetic or therapeutic profiles), and exploiting disease commonalities may significantly enhance the performance of GP methods...
October 2017: Artificial Intelligence in Medicine
journal
journal
30252
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"