797 research outputs found
The new medical model: a renewed challenge for biomedicine
Over the past 25 years, several new “medicines” have come screeching onto health care’s various platforms, including narrative medicine, personalized medicine, precision medicine and person-centred medicine. Philosopher Miriam Solomon calls the first three of these movements different “ways of knowing” or “methods,” and argues that they are each a response to shortcomings of methods that came before them. They should also be understood as reactions to the current dominant model of medicine. In this article, I will describe our dominant model, which I call “the new medical model.” I will argue that several towering problems in modern medicine can be traced to its philosophical foundations, which calls for philosophical analysis
Epidemiologic Evidence: Use at Your Own Risk?
What meaning does epidemiologic evidence have for the individual? In evidence-based medicine, epidemiologic evidence measures the patient’s risk of the outcome or the change in their risk due to an intervention. The patient’s risk is commonly understood as an individual probability. The problem of understanding epidemiologic evidence and risk thus becomes the challenge of interpreting individual patient probabilities. I argue that the patient’s risk is interpreted ontically, as a propensity. After exploring formidable problems with this interpretation in the medical context, I propose an epistemic reinterpretation of individual patient probabilities as credences. On this view, epidemiologic evidence informs medical uncertainty
Epidemiologic Evidence: Use at Your Own Risk?
What meaning does epidemiologic evidence have for the individual? In evidence-based medicine, epidemiologic evidence measures the patient’s risk of the outcome or the change in their risk due to an intervention. The patient’s risk is commonly understood as an individual probability. The problem of understanding epidemiologic evidence and risk thus becomes the challenge of interpreting individual patient probabilities. I argue that the patient’s risk is interpreted ontically, as a propensity. After exploring formidable problems with this interpretation in the medical context, I propose an epistemic reinterpretation of individual patient probabilities as credences. On this view, epidemiologic evidence informs medical uncertainty
Two Valid Approaches for Determining Whether “Taxes” Get Priority in Bankruptcy Cases
(Excerpt)
In bankruptcies, tax status often effects whether claims are entitled to priority. Thus, debates about whether charges are penalties or taxes date back to the early twentieth century. In 1930, the Supreme Court established that courts are not bound to the characterization given to a charge by the municipality that created it. Rather, courts have a duty to consider the “real nature” and “effect” of the charge. Accordingly, different circuits have implemented different approaches to make these determinations.
This Article examines the ambiguity among circuits regarding charges’ “tax” status and resulting priority entitlement. Part I outlines In re Lorber’s multi-factor test in the Ninth Circuit. Part II outlines In re Peete’s functional examination test in the Seventh Circuit. Part III examines the tests’ similarities and differences. The Article concludes by contextualizing the concurrent validity of both approaches
Epidemiologic Evidence: Use at Your Own Risk?
What meaning does epidemiologic evidence have for the individual? In evidence-based medicine, epidemiologic evidence measures the patient’s risk of the outcome or the change in their risk due to an intervention. The patient’s risk is commonly understood as an individual probability. The problem of understanding epidemiologic evidence and risk thus becomes the challenge of interpreting individual patient probabilities. I argue that the patient’s risk is interpreted ontically, as a propensity. After exploring formidable problems with this interpretation in the medical context, I propose an epistemic reinterpretation of individual patient probabilities as credences. On this view, epidemiologic evidence informs medical uncertainty
A Misuse-Based Intrusion Detection System for ITU-T G.9959 Wireless Networks
Wireless Sensor Networks (WSNs) provide low-cost, low-power, and low-complexity systems tightly integrating control and communication. Protocols based on the ITU-T G.9959 recommendation specifying narrow-band sub-GHz communications have significant growth potential. The Z-Wave protocol is the most common implementation. Z-Wave developers are required to sign nondisclosure and confidentiality agreements, limiting the availability of tools to perform open source research. This work discovers vulnerabilities allowing the injection of rogue devices or hiding information in Z-Wave packets as a type of covert channel attack. Given existing vulnerabilities and exploitations, defensive countermeasures are needed. A Misuse-Based Intrusion Detection System (MBIDS) is engineered, capable of monitoring Z-Wave networks. Experiments are designed to test the detection accuracy of the system against attacks. Results from the experiments demonstrate the MBIDS accurately detects intrusions in a Z-Wave network with a mean misuse detection rate of 99%. Overall, this research contributes new Z-Wave exploitations and an MBIDS to detect rogue devices and packet injection attacks, enabling a more secure Z-Wave network
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