Closing the gap in surveillance and audit of invasive mold diseases for antifungal stewardship using machine learning

Clinical audit of invasive mold disease (IMD) in hematology patients is inefficient due to the difficulties of case finding. This results in antifungal stewardship (AFS) programs preferentially reporting drug cost and consumption rather than measures that actually reflect quality of care. We used machine learning-based natural language processing (NLP) to non-selectively screen chest tomography (CT) reports for pulmonary IMD, verified by clinical review against international definitions and benchmarked against key AFS measures. NLP screened 3014 reports from 1 September 2008 to 31 December 2017, generating 784 positives that after review, identified 205 IMD episodes (44% probable-proven) in 185 patients from 50,303 admissions. Breakthrough-probable/proven-IMD on antifungal prophylaxis accounted for 60% of episodes with serum monitoring of voriconazole or posaconazole in the 2 weeks prior performed in only 53% and 69% of episodes, respectively. Fiberoptic bronchoscopy within 2 days of CT scan occurred in only 54% of episodes. The average turnaround of send-away bronchoalveolar galactomannan of 12 days (range 7-22) was associated with high empiric liposomal amphotericin consumption. A random audit of 10% negative reports revealed two clinically significant misses (0.9%, 2/223). This is the first successful use of applied machine learning for institutional IMD surveillance across an entire hematology population describing process and outcome measures relevant to AFS. Compared to current methods of clinical audit, semi-automated surveillance using NLP is more efficient and inclusive by avoiding restrictions based on any underlying hematologic condition, and has the added advantage of being potentially scalable

Histories of Australian Rock Art Research

Australia has one of the largest inventories of rock art in the world with pictographs and petroglyphs found almost anywhere that has suitable rock surfaces – in rock shelters and caves, on boulders and rock platforms. First Nations people have been marking these places with figurative imagery, abstract designs, stencils and prints for tens of thousands of years, often engaging with earlier rock markings. The art reflects and expresses changing experiences within landscapes over time, spirituality, history, law and lore, as well as relationships between individuals and groups of people, plants, animals, land and Ancestral Beings that are said to have created the world, including some rock art. Since the late 1700s, people arriving in Australia have been fascinated with the rock art they encountered, with detailed studies commencing in the late 1800s. Through the 1900s an impressive body of research on Australian rock art was undertaken, with dedicated academic study using archaeological methods employed since the late 1940s. Since then, Australian rock art has been researched from various perspectives, including that of Traditional Owners, custodians and other community members. Through the 1900s, there was also growing interest in Australian rock art from researchers across the globe, leading many to visit or migrate to Australia to undertake rock art research. In this volume, the varied histories of Australian rock art research from different parts of the country are explored not only in terms of key researchers, developments and changes over time, but also the crucial role of First Nations people themselves in investigations of this key component of their living heritage

Natural language processing for similar languages, varieties, and dialects: A survey

There has been a lot of recent interest in the natural language processing (NLP) community in the computational processing of language varieties and dialects, with the aim to improve the performance of applications such as machine translation, speech recognition, and dialogue systems. Here, we attempt to survey this growing field of research, with focus on computational methods for processing similar languages, varieties, and dialects. In particular, we discuss the most important challenges when dealing with diatopic language variation, and we present some of the available datasets, the process of data collection, and the most common data collection strategies used to compile datasets for similar languages, varieties, and dialects. We further present a number of studies on computational methods developed and/or adapted for preprocessing, normalization, part-of-speech tagging, and parsing similar languages, language varieties, and dialects. Finally, we discuss relevant applications such as language and dialect identification and machine translation for closely related languages, language varieties, and dialects.Non peer reviewe

The Nature of attachment:An Australian experience

Throughout the world, protected area management regimes typically separate cultural and natural heritage in legislation, policy, administrative structures, disciplinary expertise, and on-ground practice. Within settler colonial nations, including Australia, cultural heritage is itself habitually separated into indigenous heritage and 'historic' (or non-indigenous) heritage. A consequence of these multiple binaries and disconnected regimes is that they work across rather than with one another. In this chapter, I use the frame of place-attachment to consider issues arising from the separation of natural and cultural heritage in the management of protected areas. The case examples are homestead gardens within protected areas, and my concern is for the recognition of Anglo-Australian place-attachment to domestic gardens.</p