Deep Learning in Cardiology

The medical field is creating large amount of data that physicians are unable to decipher and use efficiently. Moreover, rule-based expert systems are inefficient in solving complicated medical tasks or for creating insights using big data. Deep learning has emerged as a more accurate and effective technology in a wide range of medical problems such as diagnosis, prediction and intervention. Deep learning is a representation learning method that consists of layers that transform the data non-linearly, thus, revealing hierarchical relationships and structures. In this review we survey deep learning application papers that use structured data, signal and imaging modalities from cardiology. We discuss the advantages and limitations of applying deep learning in cardiology that also apply in medicine in general, while proposing certain directions as the most viable for clinical use.Comment: 27 pages, 2 figures, 10 table

Assessment Of Blood Pressure Regulatory Controls To Detect Hypovolemia And Orthostatic Intolerance

Regulation of blood pressure is vital for maintaining organ perfusion and homeostasis. A significant decline in arterial blood pressure could lead to fainting and hypovolemic shock. In contrast to young and healthy, people with impaired autonomic control due to aging or disease find regulating blood pressure rather demanding during orthostatic challenge. This thesis performed an assessment of blood pressure regulatory controls during orthostatic challenge via traditional as well as novel approaches with two distinct applications 1) to design a robust automated system for early identification of hypovolemia and 2) to assess orthostatic tolerance in humans. In chapter 3, moderate intensity hemorrhage was simulated via lower-body negative pressure (LBNP) with an aim to identify moderate intensity hemorrhage (-30 and -40 mmHg LBNP) from resting baseline. Utilizing features extracted from common vital sign monitors, a classification accuracy of 82% and 91% was achieved for differentiating -30 and -40 mmHg LBNP, respectively from baseline. In chapter 4, cause-and-effect relationship between the representative signals of the cardiovascular and postural systems to ascertain blood pressure homeostasis during standing was performed. The degree of causal interaction between the two systems, studied via convergent cross mapping (CCM), showcased the existence of a significant bi-directional interaction between the representative signals of two systems to regulate blood pressure. Therefore, the two systems should be accounted for jointly when addressing physiology behind fall. Further, in chapter 5, the potential of artificial gravity (2-g) induced via short-arm human centrifuge at feet towards evoking blood pressure regulatory controls analogous to standing was investigated. The observation of no difference in the blood pressure regulatory controls, during 2-g centrifugation compared to standing, strongly supported the hypothesis of artificial hypergravity for mitigating cardiovascular deconditioning, hence minimizing post-flight orthostatic intolerance

On entropy of probability integral transformed time series

Abstract The goal of this paper is to investigate the changes of entropy estimates when the amplitude distribution of the time series is equalized using the probability integral transformation. The data we analyzed were with known properties—pseudo-random signals with known distributions, mutually coupled using statistical or deterministic methods that include generators of statistically dependent distributions, linear and non-linear transforms, and deterministic chaos. The signal pairs were coupled using a correlation coefficient ranging from zero to one. The dependence of the signal samples is achieved by moving average filter and non-linear equations. The applied coupling methods are checked using statistical tests for correlation. The changes in signal regularity are checked by a multifractal spectrum. The probability integral transformation is then applied to cardiovascular time series—systolic blood pressure and pulse interval—acquired from the laboratory animals and represented the results of entropy estimations. We derived an expression for the reference value of entropy in the probability integral transformed signals. We also experimentally evaluated the reliability of entropy estimates concerning the matching probabilities

Delegated causality of complex systems

A notion of delegated causality is introduced here. This subtle kind of causality is dual to interventional causality. Delegated causality elucidates the causal role of dynamical systems at the “edge of chaos”, explicates evident cases of downward causation, and relates emergent phenomena to Gödel’s incompleteness theorem. Apparently rich implications are noticed in biology and Chinese philosophy. The perspective of delegated causality supports cognitive interpretations of self-organization and evolution

HUMAN CARDIOVASCULAR RESPONSES TO SIMULATED PARTIAL GRAVITY AND A SHORT HYPERGRAVITY EXPOSURE

Orthostatic intolerance (OI), i.e., the inability to maintain stable arterial pressure during upright posture, is a major problem for astronauts after spaceflight. Therefore, one important goal of spaceflight-related research is the development of countermeasures to prevent post flight OI. Given the rarity and expense of spaceflight, countermeasure development requires ground-based simulations of partial gravity to induce appropriate orthostatic effects on the human body, and to test the efficacy of potential countermeasures. To test the efficacy of upright lower body positive pressure (LBPP) as a model for simulating cardiovascular responses to lunar and Martian gravities on Earth, cardiovascular responses to upright LBPP were compared with those of head-up tilt (HUT), a well-accepted simulation of partial gravity, in both ambulatory and cardiovascularly deconditioned subjects. Results indicate that upright LBPP and HUT induced similar changes in cardiovascular regulation, supporting the use of upright LBPP as a potential model for simulating cardiovascular responses to standing and moving in lunar and Martian gravities. To test the efficacy of a short exposure to artificial gravity (AG) as a countermeasure to spaceflight-induced OI, orthostatic tolerance limits (OTL) and cardiovascular responses to orthostatic stress were tested in cardiovascularly deconditioned subjects, using combined 70º head-up tilt and progressively increased lower body negative pressure, once following 90 minutes AG exposure and once following 90 minutes of -6º head-down bed rest (HDBR). Results indicate that a short AG exposure increased OTL of cardiovascularly deconditioned subjects, with increased baroreflex and sympathetic responsiveness, compared to those measured after HDBR exposure. To gain more insight into mechanisms of causal connectivity in cardiovascular and cardiorespiratory oscillations during orthostatic challenge in both ambulatory and cardiovascularly deconditioned subjects, couplings among R-R intervals (RRI), systolic blood pressure (SBP) and respiratory oscillations in response to graded HUT and dehydration were studied using a phase synchronization approach. Results indicate that increasing orthostatic stress disassociated interactions among RRI, SBP and respiration, and that dehydration exacerbated the disconnection. The loss of causality from SBP to RRI following dehydration suggests that dehydration also reduced involvement of baroreflex regulation, which may contribute to the increased occurrence of OI

Brain Tumour Classification Using Deep Features from Structural MRI

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Development of Animal Models to Test the Fundamental Basis of Gene–Environment Interactions

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/93738/1/oby.2008.513.pd