RadSpeech's mobile dialogue system for radiologists

Sonntag, Daniel; Schulz, Christian; Reuschling, Christian; Galárraga, Luis

doi:10.1145/2166966.2167031

Cited by 14 publications

(8 citation statements)

References 2 publications

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“…To query scientific databases, four sources have been selected: scopus 1 , acm 2 , dblp 3 , and ieee 4 . The decision on the selection of these repositories was made given their extensive coverage of well-established scientific literature in computer science.…”

Section: Search Strategymentioning

confidence: 99%

“…Conversational agents or dialogue systems have been built with several purposes; from informal chit-chat conversations [1] to more sophisticated dialogue systems that support patients on health treatments [2,3]. These systems have in common the fact that they try to reproduce the way humans communicate by mimicking cognitive aspects that are part of human' conversations.…”

Section: Introductionmentioning

confidence: 99%

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A Review of Plan-Based Approaches for Dialogue Management

Teixeira

Dragoni

2022

Cogn Comput

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Dialogue systems deliver a more natural mean of communication between humans and machines when compared to traditional systems. Beyond input/output components that understand and generate natural language utterances, the core of a dialogue system is the dialogue manager. The aim of the dialogue manager is to mimic all cognitive aspects related to a natural conversation and it is responsible for identifying the current state of the dialogue and for deciding the next action to be taken by a dialogue system. Artificial intelligence (AI) planning is one of the techniques available in the literature for dialogue management. In a dialogue system, AI planning deals with the action selection problem by treating each utterance as an action and by choosing the actions that get closer to the dialogue goal. This work aims to provide a systematic literature review (SLR) that investigates recent contributions to plan-based dialogue management. This SLR aims at answering research questions concerning: (i) the types of AI planning exploited for dialogue management; (ii) the planning characteristics that justify its adoption in dialogue system; (iii) and, the challenges posed on the development of plan-based dialogue managers. The present SLR was performed by querying four scientific repositories, followed by a manual search on works from the most eminent authors in the field. Further works that were cited by the retrieved papers were also considered for inclusion. Our final corpus is composed of forty works, including only works published since 2014. The results indicate that AI planning is still an emerging strategy for dialogue management. Although AI planning can offer a strong contribution to dialogue systems, especially to those that require predictability, some relevant challenges might still limit its adoption. Our results contributed to discussions in the field and they highlight some research gaps to be addressed in future studies.

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Section: Search Strategymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Review of Plan-Based Approaches for Dialogue Management

Teixeira

Dragoni

2022

Cogn Comput

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“…③ Dann können annotierte Datensätze zur automatischen Bild- und Videoanalyse manuell erzeugt werden („automatic image recognition, spatial reasoning“; [ 39 , 42 ]).…”

Section: Inkrementelle Wissensakquisitionunclassified

Künstliche Intelligenz in der Medizin und Gynäkologie – Holzweg oder Heilversprechen?

Sonntag

2021

Gynäkologe

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Künstliche Intelligenz (KI) hat in den letzten Jahren eine neue Reifephase erreicht und entwickelt sich zum Treiber der Digitalisierung in allen Lebensbereichen. Die KI ist eine Querschnittstechnologie, die für alle Bereiche der Medizin mit Bild‑, Text- und Biodaten von großer Bedeutung ist. Es gibt keinen medizinischen Bereich, der nicht von KI beeinflusst werden wird. Dabei spielt die klinische Entscheidungsunterstützung eine wichtige Rolle. KI-Methoden etablieren sich gerade beim medizinischen Workflow-Management und bei der Vorhersage des Behandlungserfolgs bzw. des Behandlungsergebnisses. KI-Systeme können bereits in Bilddiagnose und im Patientenmanagement unterstützen, aber keine kritischen Entscheidungen vorschlagen. Die jeweiligen Präventions- oder Therapiemaßnahmen können mit KI-Unterstützung sinnvoller bewertet werden, allerdings ist die Abdeckung der Krankheiten noch viel zu gering, um robuste Systeme für den klinischen Alltag zu erstellen. Der flächendeckende Einsatz setzt Fortbildungsmaßnahmen für Ärzte voraus, um die Entscheidung treffen zu können, wann auf automatische Entscheidungsunterstützung vertraut werden kann.

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“…In this paper, we discuss the design and implementation of a first Medical Multimodal Cyber-Physical Environment and focus on how situation awareness meets mutual knowledge, which is defined by grounded knowledge the cyber-physical environment and the user are both aware of as context features which are obtained from sensor interpretation and database lookups for a resulting medical augmented cognition application. [19], DigitalPen [22], Radspeech [20], ERmed/ERglasses, the focus of this paper according to the emphasis on augmented reality for augmented cognition, MediVa (a touch screen installation), and SmartPen [11] 2 Background…”

Section: Introductionmentioning

confidence: 99%

ERmed – Towards Medical Multimodal Cyber-Physical Environments

Sonntag

2014

Foundations of Augmented Cognition. Advancing Human Performance and Decision-Making Through Adaptive Systems

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With new technologies towards medical cyber-physical systems, such as networked head-mounted displays (HMDs) and eye trackers, new interaction opportunities arise for real-time interaction between cyber-physical systems and users. This leads to cyber-physicial environments in which the user has an active role to play inside the cyberphysical system. With our medical application in the context of a cancer screening programme, we are combining active speech based input, passive/active eye tracker user input, and HMD output (all devices are onbody and hands-free) in a convenient way for both the patient and the doctor inside such a medical cyber-physical system. In this paper, we discuss the design and implementation of our resulting Medical Multimodal Cyber-Physical Environment and focus on how situation awareness provided by the environmental sensors effectively leads to an augmented cognition application for the doctor.

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RadSpeech's mobile dialogue system for radiologists

Cited by 14 publications

References 2 publications

A Review of Plan-Based Approaches for Dialogue Management

A Review of Plan-Based Approaches for Dialogue Management

Künstliche Intelligenz in der Medizin und Gynäkologie – Holzweg oder Heilversprechen?

ERmed – Towards Medical Multimodal Cyber-Physical Environments

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