Stefania Montani – författare

This book constitutes the refereed post-conference proceedings of the First International Workshop on Artificial Intelligence in Health, AIH 2018, in Stockholm, Sweden, in July 2018. This workshop consolidated the workshops CARE, KRH4C and AI4HC into a single event.The 18 revised full papers included in this volume were carefully selected from the 26 papers accepted for presentation out of 42 initial submissions. The papers present AI technologies with medical applications and are organized in three tracks: agents in healthcare; data science and decision systems in medicine; and knowledge management in healthcare.

This book constitutes the refereed post-conference proceedings of the First International Workshop on Artificial Intelligence in Health, AIH 2018, in Stockholm, Sweden, in July 2018. This workshop consolidated the workshops CARE, KRH4C and AI4HC into a single event.The 18 revised full papers included in this volume were carefully selected from the 26 papers accepted for presentation out of 42 initial submissions. The papers present AI technologies with medical applications and are organized in three tracks: agents in healthcare; data science and decision systems in medicine; and knowledge management in healthcare.

Case-based reasoning (CBR) is an Artificial Intelligence (AI) technique to support the capability of reasoning and learning in advanced decision support systems. CBR exploits the specific knowledge collected on previously encountered and solved situations, which are known as cases.In this book, we have collected a selection of papers on very recent CBR applications. These, after an in-depth analysis of their specific application domain needs, propose proper methodological solutions and give encouraging evaluation results, which have in some cases led to the commercialization step. The collected contributions demonstrate the capability of CBR to solve or handle issues which would be too difficult to manage with other classical AI methods and techniques, such as rules or models. The heterogeneity of the involved application domains indicates the flexibility of CBR, and its applicability in all those fields where experiential knowledge is (readily) available.

Case-based reasoning (CBR) is an Artificial Intelligence (AI) technique to support the capability of reasoning and learning in advanced decision support systems. CBR exploits the specific knowledge collected on previously encountered and solved situations, which are known as cases.In this book, we have collected a selection of papers on very recent CBR applications. These, after an in-depth analysis of their specific application domain needs, propose proper methodological solutions and give encouraging evaluation results, which have in some cases led to the commercialization step. The collected contributions demonstrate the capability of CBR to solve or handle issues which would be too difficult to manage with other classical AI methods and techniques, such as rules or models. The heterogeneity of the involved application domains indicates the flexibility of CBR, and its applicability in all those fields where experiential knowledge is (readily) available.

The International Conference on Case-Based Reasoning (ICCBR) is the preeminentinternationalmeetingoncase-basedreasoning(CBR). Through2009, ICCBR (http://www. iccbr. org) had been a biennial conference, held in alter- tion with its sister conference, the European Conference on Case-BasedReas- ing (http://www. eccbr. org), which was located in Europe. At the 2009 ICCBR,the ICCBR ProgramCommittee elected to extend ano?er of consoli- tion with ECCBR. The o?er was accepted by the ECCBR 2010 organizers and they have considered it approved by the ECCBR community, as the two conf- ences share a majority of Program Committee members. ICCBR and ECCBR havebeen theleading conferencesonCBR. From2010,ICCBRandECCBRwill be merged in a single conference series, called ICCBR. As there had been eight previous ICCBR events and nine previous ECCBR events, the combined series is considered the 18th ICCBR. ICCBR 2010 (http://www. iccbr. org/iccbr10) was therefore the 18th in this seriesof internationalconferenceshighlighting the mostsigni?cantcontributions tothe?eldofCBR.TheconferencetookplaceduringJuly19-22,2010inthecity of Alessandria,Italy, on the beautiful campus of the University of Piemonte O- entale "A. Avogadro. " Previous ICCBR conferences were held in Sesimbra, P- tugal(1995),Providence,RhodeIsland,USA(1997),SeeonMonastery,Germany (1999), Vancouver, BC, Canada (2001), Trondheim, Norway (2003), Chicago, Illinois, USA (2005), Belfast, Northern Ireland (2007), and Seattle, Washington, USA (2009). Day 1 of the conference hosted an Applications Track, the second Doctoral Consortium, and the third Computer Cooking Contest. The Applications Track featured ?elded applications and CBR systems demos in industrial and scienti?c settingswithanemphasis ondiscussionandnetworkingbetweenresearchersand industrials.

Case-based reasoning (CBR) is an Artificial Intelligence (AI) technique to support the capability of reasoning and learning in advanced decision support systems. CBR exploits the specific knowledge collected on previously encountered and solved situations, which are known as cases.In this book, we have collected a selection of papers on very recent CBR applications. These, after an in-depth analysis of their specific application domain needs, propose proper methodological solutions and give encouraging evaluation results, which have in some cases led to the commercialization step. The collected contributions demonstrate the capability of CBR to solve or handle issues which would be too difficult to manage with other classical AI methods and techniques, such as rules or models. The heterogeneity of the involved application domains indicates the flexibility of CBR, and its applicability in all those fields where experiential knowledge is (readily) available.

Case-based reasoning paradigms offer automatic reasoning capabilities which are useful for the implementation of human like machines in a limited sense. This research book is the second volume in a series devoted to presenting Case-based reasoning (CBR) applications. The first volume, published in 2010, testified the flexibility of CBR, and its applicability in all those fields where experiential knowledge is available. This second volume further witnesses the heterogeneity of the domains in which CBR can be exploited, but also reveals some common directions that are clearly emerging in recent years. This book will prove useful to the application engineers, scientists, professors and students who wish to develop successful case-based reasoning applications.