Artificial diagnosis of sensory taints due to brettanomyces spp. contamination in Valpolicella wines

Diagnosis and intervention to avoid Brett taints in the product can be a time-consuming task for the enologist in large production facilities and an instrumental and automated detection systems assisting the local expert technician would be desirable. This paper investigates whether electronic noses, which have been tested in other wine making and classification tasks, can be of use in detecting Brett taints in Valpolicella wines

Warranted Diagnosis

A diagnostic process is an investigative process that takes a clinical picture as input and outputs a diagnosis. We propose a method for distinguishing diagnoses that are warranted from those that are not, based on the cognitive processes of which they are the outputs. Processes designed and vetted to reliably produce correct diagnoses will output what we shall call ‘warranted diagnoses’. The latter are diagnoses that should be trusted even if they later turn out to have been wrong. Our work is based on the recently developed Cognitive Process Ontology and further develops the Ontology of General Medical Science. It also has applications in fields such as intelligence, forensics, and predictive maintenance, all of which rely on vetted processes designed to secure the reliability of their outputs

Learning approximate diagnosis

Model-based diagnosis (MBD) provides several advantages over experiential rule-based systems. A principal shortcoming of MBD is that MBD learns nothing from any given example. An MBD system facing the same task a second time will incur the same computational effort as that incurred the first time. Our earlier work on incorporating explanation-based learning (EBL) in MBD [4] suggested a diagnostic architecture integrating EBL and MBD components. In this architecture, EBL was used to learn diagnostic rules. But the diagnoses proposed by the rules could be erroneous. So constraint suspension testing was used to check all proposed diagnoses. Insisting on perfect accuracy causes the performance of this scheme for "learning while doing" to deteriorate rapidly with the size of the device to be diagnosed. In this paper, we describe a method for trading off accuracy for efficiency. In this approach, most diagnosis problems are handled by the associational rules learned from previous problems. Model-based reasoning and learning are activated only when performance drops below a given threshold. We present empirical results on circuits of increasing number of components illustrating how this approach scales up

HIV diagnosis and disclosure

For those we interviewed the knowledge that either they or their partner had diagnosed HIV needed to be managed on both an individual and collective level. It impacted on how each partner saw themselves and also how they perceived the future of their relationship. This report begins by exploring how participants with diagnosed HIV became aware of their HIV status, and how they have tried to come to terms with it, before describing their decision making about sharing this status with their partner and their means of doing so. The thoughts and experiences of participants who had not disclosed their status are described. Finally it explores the reactions of the HIV negative or untested partners to disclosure, its impact on a personal level and how they sought to come to terms with this news

Diagnosis of South Asia Specific Diseases

Asian StudiesHindi Urdu FlagshipSouth Asia Institut