Automatic generation of textual summaries from neonatal intensive care data

Portet, François; Reiter, Ehud; Gatt, Albert; Hunter, Jim; Sripada, Somayajulu; Freer, Yvonne; Sykes, Cindy

doi:10.1016/j.artint.2008.12.002

Cited by 197 publications

(146 citation statements)

References 67 publications

Supporting

Mentioning

140

Contrasting

Unclassified

Order By: Relevance

“…200 The modules for diagnosis per se may be based on machine learning methods 201 and perhaps include an interface in natural language provided by a language generation system. 202 The computational diagnosis system must be implemented so as to acquire (and learn) new information from the present exams and analysis.…”

Section: Statistical and Computational Methodsmentioning

confidence: 99%

Nanomaterials for Diagnosis: Challenges and Applications in Smart Devices Based on Molecular Recognition

Oliveira

Iost

Siqueira

et al. 2014

ACS Appl. Mater. Interfaces

156

137

View full text Add to dashboard Cite

Clinical diagnosis has always been dependent on the efficient immobilization of biomolecules in solid matrices with preserved activity, but significant developments have taken place in recent years with the increasing control of molecular architecture in organized films. Of particular importance is the synergy achieved with distinct materials such as nanoparticles, antibodies, enzymes, and other nanostructures, forming structures organized on the nanoscale. In this review, emphasis will be placed on nanomaterials for biosensing based on molecular recognition, where the recognition element may be an enzyme, DNA, RNA, catalytic antibody, aptamer, and labeled biomolecule. All of these elements may be assembled in nanostructured films, whose layer-by-layer nature is essential for combining different properties in the same device. Sensing can be done with a number of optical, electrical, and electrochemical methods, which may also rely on nanostructures for enhanced performance, as is the case of reporting nanoparticles in bioelectronics devices. The successful design of such devices requires investigation of interface properties of functionalized surfaces, for which a variety of experimental and theoretical methods have been used. Because diagnosis involves the acquisition of large amounts of data, statistical and computational methods are now in widespread use, and one may envisage an integrated expert system where information from different sources may be mined to generate the diagnostics.

show abstract

Section: Statistical and Computational Methodsmentioning

confidence: 99%

Nanomaterials for Diagnosis: Challenges and Applications in Smart Devices Based on Molecular Recognition

Oliveira

Iost

Siqueira

et al. 2014

ACS Appl. Mater. Interfaces

156

137

View full text Add to dashboard Cite

show abstract

“…Gatt et al [18,37] have built a natural language generation system for intensive care units. This system can automatically generate textual summaries from the patient's medical data, e.g., by reporting that SpO2 increased from 88% to 97% between 3:00 am and 6:00 am.…”

Section: Clinical Natural Language Generation Systemsmentioning

confidence: 99%

Triggers and Monitoring in Intelligent Personal Health Record

Luo¹

2011

J Med Syst

View full text Add to dashboard Cite

Although Web-based personal health records (PHRs) have been widely deployed, the existing ones have limited intelligence. Previously, we introduced expert system technology and Web search technology into the PHR domain and proposed the concept of an intelligent PHR (iPHR). iPHR provides personalized healthcare information to facilitate users' daily activities of living. The current iPHR is passive and follows the pull model of information distribution. This paper introduces triggers and monitoring into iPHR to make iPHR become active. Our idea is to let medical professionals pre-compile triggers and store them in iPHR's knowledge base. Each trigger corresponds to an abnormal event that may have potential medical impact. iPHR keeps collecting, processing, and analyzing the user's medical data from various sources such as wearable sensors. Whenever an abnormal event is detected from the user's medical data, the corresponding trigger fires and the related personalized healthcare information is pushed to the user using natural language generation technology, expert system technology, and Web search technology.

show abstract

“…For instance, the BT-45 system [39] returns "Fi02 increased so saturation rose" if a causality is identified between "increase FiO2" and "saturation rise".…”

Section: Sentence Inferencementioning

confidence: 99%

Interpretability of fuzzy linguistic summaries

Lesot

Moyse

Bouchon‐Meunier

2016

Fuzzy Sets and Systems

View full text Add to dashboard Cite

This paper investigates the question of the interpretability of fuzzy linguistic summaries, both at the sentence level and at the summary level, seen as a set of sentences. The individual sentence interpretability is examined as depending both on its representativity measured by a quality degree and on its linguistic expression. Different properties at the summary level are also discussed, namely their consistency, their non redundancy and the information they convey.

show abstract

Automatic generation of textual summaries from neonatal intensive care data

Cited by 197 publications

References 67 publications

Nanomaterials for Diagnosis: Challenges and Applications in Smart Devices Based on Molecular Recognition

Nanomaterials for Diagnosis: Challenges and Applications in Smart Devices Based on Molecular Recognition

Triggers and Monitoring in Intelligent Personal Health Record

Interpretability of fuzzy linguistic summaries

Contact Info

Product

Resources

About