Towards autonomous diagnostic systems with medical imaging

Democratizing access to high quality healthcare has highlighted the need for autonomous diagnostic systems that a non-expert can use. Remote communities, first responders and even deep space explorers will come to rely on medical imaging systems that will provide them with Point of Care diagnostic capabilities. This thesis introduces the building blocks that would enable the creation of such a system. Firstly, we present a case study in order to further motivate the need and requirements of autonomous diagnostic systems. This case study primarily concerns deep space exploration where astronauts cannot rely on communication with earth-bound doctors to help them through diagnosis, nor can they make the trip back to earth for treatment. Requirements and possible solutions about the major challenges faced with such an application are discussed. Moreover, this work describes how a system can explore its perceived environment by developing a Multi Agent Reinforcement Learning method that allows for implicit communication between the agents. Under this regime agents can share the knowledge that benefits them all in achieving their individual tasks. Furthermore, we explore how systems can understand the 3D properties of 2D depicted objects in a probabilistic way. In Part II, this work explores how to reason about the extracted information in a causally enabled manner. A critical view on the applications of causality in medical imaging, and its potential uses is provided. It is then narrowed down to estimating possible future outcomes and reasoning about counterfactual outcomes by embedding data on a pseudo-Riemannian manifold and constraining the latent space by using the relativistic concept of light cones. By formalizing an approach to estimating counterfactuals, a computationally lighter alternative to the abduction-action-prediction paradigm is presented through the introduction of Deep Twin Networks. Appropriate partial identifiability constraints for categorical variables are derived and the method is applied in a series of medical tasks involving structured data, images and videos. All methods are evaluated in a wide array of synthetic and real life tasks that showcase their abilities, often achieving state-of-the-art performance or matching the existing best performance while requiring a fraction of the computational cost.Open Acces

A PROBABILISTIC APPROACH TO DATA INTEGRATION IN BIOMEDICAL RESEARCH: THE IsBIG EXPERIMENTS

Indiana University-Purdue University Indianapolis (IUPUI)Biomedical research has produced vast amounts of new information in the last decade but has been slow to find its use in clinical applications. Data from disparate sources such as genetic studies and summary data from published literature have been amassed, but there is a significant gap, primarily due to a lack of normative methods, in combining such information for inference and knowledge discovery. In this research using Bayesian Networks (BN), a probabilistic framework is built to address this gap. BN are a relatively new method of representing uncertain relationships among variables using probabilities and graph theory. Despite their computational complexity of inference, BN represent domain knowledge concisely. In this work, strategies using BN have been developed to incorporate a range of available information from both raw data sources and statistical and summary measures in a coherent framework. As an example of this framework, a prototype model (In-silico Bayesian Integration of GWAS or IsBIG) has been developed. IsBIG integrates summary and statistical measures from the NIH catalog of genome wide association studies (GWAS) and the database of human genome variations from the international HapMap project. IsBIG produces a map of disease to disease associations as inferred by genetic linkages in the population. Quantitative evaluation of the IsBIG model shows correlation with empiric results from our Electronic Medical Record (EMR) – The Regenstrief Medical Record System (RMRS). Only a small fraction of disease to disease associations in the population can be explained by the linking of a genetic variation to a disease association as studied in the GWAS. None the less, the model appears to have found novel associations among some diseases that are not described in the literature but are confirmed in our EMR. Thus, in conclusion, our results demonstrate the potential use of a probabilistic modeling approach for combining data from disparate sources for inference and knowledge discovery purposes in biomedical research

Rethinking Causality, Complexity and Evidence for the Unique Patient

This open access book is a unique resource for health professionals who are interested in understanding the philosophical foundations of their daily practice. It provides tools for untangling the motivations and rationality behind the way medicine and healthcare is studied, evaluated and practiced. In particular, it illustrates the impact that thinking about causation, complexity and evidence has on the clinical encounter. The book shows how medicine is grounded in philosophical assumptions that could at least be challenged. By engaging with ideas that have shaped the medical profession, clinicians are empowered to actively take part in setting the premises for their own practice and knowledge development. Written in an engaging and accessible style, with contributions from experienced clinicians, this book presents a new philosophical framework that takes causal complexity, individual variation and medical uniqueness as default expectations for health and illness

A HYBRID METHODOLOGY FOR MODELING RISK OF ADVERSE EVENTS IN COMPLEX HEALTHCARE SETTINGS

Despite efforts to provide safe, effective medical care, adverse events still occur with some regularity. While risk cannot be entirely eliminated from healthcare activities, an important goal is to develop effective and durable mitigation strategies to render the system `safer'. In order to do this, though, we must develop models that comprehensively and realistically characterize the risk. In the healthcare domain, this can be extremely challenging due to the wide variability in the way that healthcare processes and interventions are executed and also due to the dynamic nature of risk in this particular domain. In this study we have developed a generic methodology for evaluating dynamic changes in adverse event risk in acute care hospitals as a function of organizational and non-organizational factors, using a combination of modeling formalisms. First, a system dynamics (SD) framework is used to demonstrate how organizational level and policy level contributions to risk evolve over time, and how policies and decisions may affect the general system-level contribution to adverse event risk. It also captures the feedback of organizational factors and decisions over time and the non-linearities in these feedback effects. Second, Bayesian Belief Network (BBN) framework is used to represent patient-level factors and also physician level decisions and factors in the management of an individual patient, which contribute to the risk of hospital-acquired adverse event. The model is intended to support hospital decisions with regards to staffing, length of stay, and investment in safeties, which evolve dynamically over time. The methodology has been applied in modeling the two types of common adverse events; pressure ulcers and vascular catheter-associated infection, and has been validated with eight years of clinical data

Rethinking Causality, Complexity and Evidence for the Unique Patient

This open access book is a unique resource for health professionals who are interested in understanding the philosophical foundations of their daily practice. It provides tools for untangling the motivations and rationality behind the way medicine and healthcare is studied, evaluated and practiced. In particular, it illustrates the impact that thinking about causation, complexity and evidence has on the clinical encounter. The book shows how medicine is grounded in philosophical assumptions that could at least be challenged. By engaging with ideas that have shaped the medical profession, clinicians are empowered to actively take part in setting the premises for their own practice and knowledge development. Written in an engaging and accessible style, with contributions from experienced clinicians, this book presents a new philosophical framework that takes causal complexity, individual variation and medical uniqueness as default expectations for health and illness

Bone and Phosphate in Relation to Health, Survival and Genetic Factors

In this thesis, we found that a) low bone mineral density was related to increased mortality from chronic obstructive pulmonary disease and b) increased serum phosphate, even at normal levels, was related to fracture risk, low BMD at the lumbar spine and coronary artery calcification. For the latter association, we found evidence of causality, due to the implementation of Mendelian Randomization technique. All our results were more consistent or even unique in men. The genetic analyses on phosphate levels identified 264 loci in the human genome and highlighted the importance of the Major Histocompatibility Complex (6p21.3) also on phosphate levels, as the top hit mapped to the flanking region of the MHC. Interestingly, the same finding has been described in White British and East Asian Japanese populations. Our next step will be the replication in BioBank Japan followed by trans-ethnic meta-analysis and Bayesian fine-mapping

Phylogeny, divergence time estimates and systematics of African cichlids (Cichlidae: Pseudocrenilabrinae), with a focus on the rheophilic cichlids of East and Central Africa

The teleost family Cichlidae (Teleostei: Percomorphaceae), comprising almost two thousand described species, clearly ranks among the largest fish families. Their outstanding morphological, behavioral and ecological diversity and their propensity to generate adaptive radiations made cichlids prime model systems in various fields of biology. Consequently, tremendous efforts have been devoted into the reconstruction of their evolutionary history, albeit with yet partial success. The relationships between major lineages of the megadiverse East African cichlid radiation (EAR) as well as the precise reconstruction of their evolutionary time line remain still hotly debated. This apparent intractability can be partially attributed to their complex evolutionary history, which includes phases of ancient hybridization leading to massive introgression, and to the rapid origin of multiple major lineages. The reconstruction of the spatio-temporal scene that enabled the evolutionary success of African austrotilapiine cichlids is further hampered by the yet unsettled age of the origin of the family Cichlidae, which is due to the paucity of suitable calibration points. This dissertation focuses on the evolutionary history of African austrotilapiine cichlids (Pseudocrenilabrinae), with particular attention to the riverine haplochromine lineages from Southern-Central Africa. In contrast to the famous EAR of the African Great Lakes, their riverine precursor lineages have been considerably less well studied, which applies both to their phylogenetic relationships as well as to their systematics and taxonomy. The first section of this thesis concentrates on the classification and taxonomy of several riverine cichlid lineages endemic to the Upper Congo drainage as well as on selected taxa of neighbouring Lake Tanganyika (chapters 1 – 3). In total, eight new species and two new genera were described including one ancient member of the EAR, a Hemibates species from Lake Tanganyika. Further five species of the rheophilic genus Orthochromis are described from isolated rivers from the southeastern Democratic Republic of the Congo (DRC) and Zambia, and finally two new species belonging to two new genera Lufubuchromis and Palaeoplex. The latter are endemic to two neighbouring areas in northeastern Zambia. These descriptions represent an important contribution to the knowledge on the still underexplored cichlid diversity of the Katanga-Chambeshi region (see discussion). The second section provides new insights into the complex phylogenetic history of African cichlids related to the EAR. They are analyzed and presented in the geomorphological context of the palaeo-drainage evolution of the East African Rift and tectonically related areas (chapters 4 – 5 & discussion). First, new divergence age estimates were obtained for the phylogeny of the family Cichlidae and particularly for austrotilapiine Pseudocrenilabrinae. These are based on an extensive mitogenomic data set with DNA sequences of ten protein coding genes from 180 cichlid species. The corresponding molecular clock analyses were conservatively constrained by carefully selected calibration points including six fossils and one geological event. The divergence of the monophyletic African Pseudocrenilabrinae and American Cichlinae was dated to the Late Cretaceous, thus tentatively supporting the “Marine Dispersal Hypothesis” and thus contradicting a strict Gondwana-break up scenario for the origin of the two continental cichlid radiations. In the same analyses the origin of the EAR was dated to as early as of Late Eocene/Early Oligocene age, and more importantly, the divergence ages of multiple endemic Lake Tanganyika cichlid tribes were firmly estimated to predate the formation of extant Lake Tanganyika basin itself. This result supports the recently suggested “Melting-pot Tanganyika hypothesis”, which hypothesized Lake Tanganyika to be a comparatively young reservoir of lineages partially originating from hybridization of more ancient precursor lineages. Finally, a refined and comprehensive phylogenetic hypothesis based on a comprehensive genomic nuclear DNA (ddRAD) dataset is provided for all major australotilapiine cichlid lineages related to the EAR. This massive dataset not only includes representatives of all major lacustrine tribes and lineages but particularly all potential riverine precursor lineages, altogether 206 specimens from 160 species. This dataset, in combination with a further increased taxon-sampling of the mitogenomic dataset, now with about 330 cichlid species, was used to infer candidate ancient hybridization events among australotilapiines lineages that may have contributed to the complex network-like evolutionary history and success of the EAR. This was done applying statistical methods previously applied to reconstruct the equally complex human phylogenetic history, i.e. the so-called D-statistics or the genomic evaluation of cyto-nuclear discordances. Apart from many previously reported candidate cases of ancient hybridization, numerous new ones were detected especially within major haplochromine lineages. The analysis of these results in the light of recent tectonic re-arrangements in the region strongly suggest that hybridization has played an even more important role in shaping the evolutionary history of African cichlids than already presumed. An important methodogical result of the comparative mitogenomic and nuclear genomic molecular clock analyses contrasts with previous assumptions, i.e. surprisingly divergence time estimates based on mitochondrial and nuclear (ddRAD) data emerged as largely comparable across austrotilapiine cichlids and Neogene timescales.Die Knochenfischfamilie Cichlidae gehört mit fast zweitausend beschriebenen Arten eindeutig zu den größten Fischfamilien. Ihre außergewöhnliche morphologische, verhaltensbiologische und ökologische Vielfalt, als auch ihre Tendenz adaptive Radiation hervorzubringen, machte Buntbarsche zu erstklassigen Modelorganismen für verschiedenste biologische Forschungsfelder. Trotz der großen Bemühungen um die Rekonstruktion der evolutionären Entwicklungsgeschichte der Buntbarsche ist diese bis heute nicht vollständig verstanden. Dabei werden nicht nur die Verwandtschaftsverhältnisse zwischen den Haupt-Entwicklungslinien der sogenannten „East African cichlid radiation (EAR)“, sondern auch der genaue zeitliche Ablauf der Evolutionsgeschichte dieser hochdiversen Buntbarschgruppe kontrovers diskutiert. Die Rekonstruktion der räumlich-zeitlichen Prozesse, die den evolutionären Erfolg der afrikanischen austrotilapiinen Buntbarsche ermöglichten, wird auch durch das noch immer ungeklärte Entstehungsalter sowie durch den bisher nicht präzisierten zeitlichen Ursprung der Familie Cichlidae erschwert. Der Grund dafür ist teilweise auf den Mangel geeigneter Kalibrierungspunkte für entsprechende Rekonstruktionen zurückzuführen. Die vorgelegte Dissertation beschäftigt sich primär mit der Evolutionsgeschichte afrikanischer austrotilapiiner Buntbarsche mit einem besonderem Fokus auf die fluviatilen haplochrominen Buntbarsch-Linien des südlichen Zentralafrikas. Im Gegensatz zu den berühmten Entwicklungslinien der EAR in den Grabenbruchseen Ostafrikas, wurden den fluviatilen Linien der EAR und ihrer Vorläuferlinien bedeutend weniger Beachtung geschenkt. Dies betrifft sowohl die Erforschung der phylogenetischen Verwandtschaftsverhältnisse, als auch ihre Systematik und Taxonomie. Der erste Abschnitt dieser Dissertation befasst sich daher mit der systematischen Einordnung und der Taxonomie mehrerer fluviatiler Buntbarschlinien, allesamt Endemiten des oberen Einzugsgebiets des Kongo, als auch ausgewählter Taxa aus dem benachbarten Tanganjikasee (Kapitel 1 – 3). Insgesamt wurden acht neue Arten sowie zwei neue Gattungen beschrieben. Darunter eine neue Hemibates Art aus dem Tanganjikasee, die einer alten Linie (Tribus) der EAR angehört. Außerdem wurden fünf Arten der rheophilen Gattung Orthochromis beschrieben, die in verschiedenen isolierten Flusssystemen Sambias und der südöstlichen Demokratischen Republik Kongo (DRC) vorkommen. Weiter wurden zwei neue Arten beschrieben, die jeweils ebenfalls zwei neu aufgestellten Gattungen Lufubuchromis und Palaeoplex angehören. Diese Beschreibungen stellen einen wichtigen Beitrag zur Erfassung der bis heute wenig erforschten Diversität der Buntbarsche der Katanga-Chambeshi Region dar (siehe Diskussion). Der zweite Abschnitt liefert neue Erkenntnisse über die komplexen phylogenetischen Zusammenhänge der afrikanischen Buntbarsche aus der Verwandtschaftsgruppe der EAR. Diese wurden im Kontext der Entwicklung der Paläo-Flusssysteme des ostafrikanischen Grabenbruchs sowie tektonisch angrenzender Gebiete analysiert und präsentiert (Kapitel 4 – 5 & Diskussion). Dabei wurden zuerst neue Altersabschätzungen für die Phylogenie der Buntbarsche und insbesondere der austrotilapiiner Pseudocrenilabrinae berechnet. Diese basieren auf einem umfangreichen mito-genomischen Datensatz, der DNS Sequenzen von zehn proteincodierenden Genen von 180 Buntbarscharten umfasst. Die „Molekulare Uhr“ der korrespondierenden altersabschätzenden Analysen wurde dabei mittels vorsichtig ausgewählter Kalibrierungspunkte kalibriert, darunter sechs Fossilien sowie ein geologisches Ereignis. Dabei wurde das Divergenzereignis zwischen den jeweils monophyletischen afrikanischen Pseudocrenilabrinae sowie der amerikanischen Cichlinae als in der Oberkreide liegend datiert. Dies spricht zumindest vorläufig für die sogenannte „Marine Dispersal Hypothesis“ und widerspricht somit der Annahme, dass die Divergenz der beiden kontinentalen Buntbarschradiationen direkt auf dem Auseinanderbrechen von Gondwana basiert. In der gleichen Analyse wurde der Ursprung der EAR in das späte Eozän bis frühes Oligozän datiert. Darüber hinaus wurde das Divergenzalter mehrerer im Tanganjikasee endemischer Triben als deutlich älter als die Entstehung des rezenten Tanganjikasee-Beckens selbst abgeschätzt. Dies unterstützt die vor kurzem vorgeschlagene „Melting-pot Tanganyika“-Hypothese, die formuliert, dass der Tanganjikasee ein verhältnismäßig junges Reservoir für verschiedene evolutionär alte Linien sowie Linien, die aus Hybridisierungen ebendieser hervorgegangen sind darstellt. Des Weiteren wurde basierend auf einem umfangreichen kerngenomischen DNS (ddRAD) Datensatz eine überarbeitete und umfassende Phylogenie der australotilapiinen Buntbarsche erstellt. Der Datensatz bestand aus 206 Individuen, die 160 Arten zugeordnet werden, und enthielt dabei nicht nur Vertreter aller lakustrischen Triben und Linien der EAR, sondern auch Vertreter aller potentieller Vorgängerlinien aus den Flüssen. In Kombination mit einem noch weiter vergrößerten mitochondrialen Datensatz, der etwa 330 Buntbarscharten berücksichtige, wurde der kerngenomische Datensatz genutzt um potentielle alte Hybridisations-Ereignisse zwischen den australotilapiinen Linien zu detektieren. Diese könnten möglicherweise nicht nur den evolutionären Erfolg der EAR erklären, sondern auch ihre komplexen, teilweise retikulären Verwandtschaftsverhältnisse. In dieser Teilstudie wurden vor allem statistische Analysen durchgeführt, die kürzlich zur Analyse der ebenfalls hochkomplexen Evolutionsgeschichte des Menschen zum Einsatz gekommen waren, z.B. die so genannte „D-statistics“ oder die genomische Auswertung von cyto-nuklearen Diskordanzen. Neben vielen bereits schon früher dokumentierten potentiellen alten Hybridisations-Ereignissen konnten dabei auch zahlreiche neue detektiert werden, vor allem zwischen und innerhalb der Hauptlinien des Tribus Haplochromini. Die Analyse dieser Ergebnisse im Kontext der jüngeren tektonischen Umlagerungen in der Region zeigt deutlich, dass der Hybridisierung als Evolutionsfaktor eine noch wichtigere Rolle in der Evolutionsgeschichte der afrikanischen Buntbarsche zukommt als bisher angenommen. Ein wichtiges methodisches Ergebnis resultierte aus dem Vergleich altersabschätzender Analysen, die entweder auf mitochondrialen Daten oder auf kerngenomischen Daten basierten. Entgegen früherer Annahmen, waren die korrespondierenden Altersabschätzungen der beiden Analysen für die austrotilapiinen Buntbarsche (Zeitraum: Neogen) erstaunlicherweise weitgehend miteinander vergleichbar

Enhancing Usability and Explainability of Data Systems

The recent growth of data science expanded its reach to an ever-growing user base of nonexperts, increasing the need for usability, understandability, and explainability in these systems. Enhancing usability makes data systems accessible to people with different skills and backgrounds alike, leading to democratization of data systems. Furthermore, proper understanding of data and data-driven systems is necessary for the users to trust the function of the systems that learn from data. Finally, data systems should be transparent: when a data system behaves unexpectedly or malfunctions, the users deserve proper explanation of what caused the observed incident. Unfortunately, most existing data systems offer limited usability and support for explanations: these systems are usable only by experts with sound technical skills, and even expert users are hindered by the lack of transparency into the systems\u27 inner workings and functions. The aim of my thesis is to bridge the usability gap between nonexpert users and complex data systems, aid all sort of users, including the expert ones, in data and system understanding, and provide explanations that help reason about unexpected outcomes involving data systems. Specifically, my thesis has the following three goals: (1) enhancing usability of data systems for nonexperts, (2) enable data understanding that can assist users in a variety of tasks such as achieving trust in data-driven machine learning, gaining data understanding, and data cleaning, and (3) explaining causes of unexpected outcomes involving data and data systems. For enhancing usability, we focus on example-driven user intent discovery. We develop systems based on example-driven interactions in two different settings: querying relational databases and personalized document summarization. Towards data understanding, we develop a new data-profiling primitive that can characterize tuples for which a machine-learned model is likely to produce untrustworthy predictions. We also develop an explanation framework to explain causes of such untrustworthy predictions. Additionally, this new data-profiling primitive enables interactive data cleaning. Finally, we develop two explanation frameworks, tailored to provide explanations in debugging data system components, including the data itself. The explanation frameworks focus on explaining the root cause of a concurrent application\u27s intermittent failure and exposing issues in the data that cause a data-driven system to malfunction

Dependencies in language: On the causal ontology of linguistic systems

Dependency is a fundamental concept in the analysis of linguistic systems. The many if-then statements offered in typology and grammar-writing imply a causally real notion of dependency that is central to the claim being made—usually with reference to widely varying timescales and types of processes. But despite the importance of the concept of dependency in our work, its nature is seldom defined or made explicit. This book brings together experts on language, representing descriptive linguistics, language typology, functional/cognitive linguistics, cognitive science, research on gesture and other semiotic systems, developmental psychology, psycholinguistics, and linguistic anthropology to address the following question: What kinds of dependencies exist among language-related systems, and how do we define and explain them in natural, causal terms