Why Technology Provides Compelling Reasons to Apply a Daubert Analysis to the Legal Standard of Care in Medical Malpractice Cases

Traditionally, courts have applied a customary practice standard in determining the legal standard of care in medical malpractice cases. Recently, a few courts have abandoned this dated standard and instead applied a Daubert analysis to the standard of care, which focuses on medical evidence that is scientifically based . In light of these recent holdings, this iBrief argues that with the increasing amounts of technologies improving evidence-based medicine, the customary practice standard is no longer a useful or appropriate test for determining the standard of care in medical malpractice cases. By applying a Daubert analysis to an expert’s testimony on the standard of care, the testimony becomes a scientifically based testimony rather than an expert’s notion of what is common practice in the medical profession

Case Base Mining for Adaptation Knowledge Acquisition

In case-based reasoning, the adaptation of a source case in order to solve the target problem is at the same time crucial and difficult to implement. The reason for this difficulty is that, in general, adaptation strongly depends on domain-dependent knowledge. This fact motivates research on adaptation knowledge acquisition (AKA). This paper presents an approach to AKA based on the principles and techniques of knowledge discovery from databases and data-mining. It is implemented in CABAMAKA, a system that explores the variations within the case base to elicit adaptation knowledge. This system has been successfully tested in an application of case-based reasoning to decision support in the domain of breast cancer treatment

Understanding the factors that influence breast reconstruction decision making in Australian women

Background Breast reconstruction is safe and improves quality of life. Despite this, many women do not undergo breast reconstruction and the reasons for this are poorly understood. This study aims to identify the factors that influence a woman's decision whether or not to have breast reconstruction and to better understand their attitudes toward reconstruction. Methodology An online survey was distributed to breast cancer patients from Breast Cancer Network Australia. Results were tabulated, described qualitatively and analyzed for significance using a multiple logistic regression model. Results 501 mastectomy patients completed surveys, of which 62% had undergone breast reconstruction. Factors that positively influenced likelihood of reconstruction included lower age, bilateral mastectomy, access to private hospitals, decreased home/work responsibilities, increased level of home support and early discussion of reconstructive options. Most common reasons for avoiding reconstruction included “I don't feel the need” and “I don't want more surgery”. The most commonly sited sources of reconstruction information came from the breast surgeon followed by the plastic surgeon then the breast cancer nurse and the most influential of these was the plastic surgeon. Conclusions A model using factors easily obtained on clinical history can be used to understand likelihood of reconstruction. This knowledge may help identify barriers to reconstruction, ultimately improving the clinicians' ability to appropriately educate mastectomy patients and ensure effective decision making around breast reconstruction

A qualitative comparison of how older breast cancer survivors process treatment information regarding endocrine therapy.

BACKGROUND:It remains unclear how information about aromatase inhibitors (AI) impacts women's decision-making about persistence with endocrine therapy. PURPOSE:To describe and compare how women treated for primary early stage breast cancer either persisting or not persisting with an AI received, interpreted, and acted upon AI-related information. DESIGN:Thematic analysis was used to sort and compare the data into the most salient themes. PARTICIPANTS:Women (N = 54; 27 persisting, 27 not persisting with an AI) aged 65-93 years took part in qualitative interviews. RESULTS:Women in both subgroups described information similarly in terms of its value, volume, type, and source. Aspects of AI-related information that either differed between the subgroups or were misunderstood by one or both subgroups included: (1) knowledge of AI or tamoxifen prior to cancer diagnosis, (2) use of online resources, (3) misconceptions about estrogen, hormone replacement therapies and AI-related symptoms, and (4) risk perception and the meaning and use of recurrence statistics such as Oncotype DX. CONCLUSIONS:Persisters and nonpersisters were similar in their desire for more information about potential side effects and symptom management at AI prescription and subsequent appointments. Differences included how information was obtained and interpreted. Interactive discussion questions are shared that can incorporate these findings into clinical settings

Explainable artificial intelligence for breast cancer: A visual case-based reasoning approach

International audienceCase-Based Reasoning (CBR) is a form of analogical reasoning in which the solution for a (new) query case is determined using a database of previous known cases with their solutions. Cases similar to the query are retrieved from the database, and then their solutions are adapted to the query. In medicine, a case usually corresponds to a patient and the problem consists of classifying the patient in a class of diagnostic or therapy. Compared to "black box" algorithms such as deep learning, the responses of CBR systems can be justified easily using the similar cases as examples. However, this possibility is often under-exploited and the explanations provided by most CBR systems are limited to the display of the similar cases. In this paper, we propose a CBR method that can be both executed automatically as an algorithm and presented visually in a user interface for providing visual explanations or for visual reasoning. After retrieving similar cases, a visual interface displays quantitative and qualitative similarities between the query and the similar cases, so as one can easily classify the query through visual reasoning, in a fully explainable manner. It combines a quantitative approach (visualized by a scatter plot based on Multidimensional Scaling in polar coordinates , preserving distances involving the query) and a qualitative approach (set visualization using rainbow boxes). We applied this method to breast cancer management. We showed on three public datasets that our qualitative method has a classification accuracy comparable to k-Nearest Neighbors algorithms, but is better explainable. We also tested the proposed interface during a small user study. Finally, we apply the proposed approach to a real dataset in breast cancer. Medical experts found the visual approach interesting as it explains why cases are similar through the visualization of shared patient characteristics

Mathematical modeling of the metastatic process

Mathematical modeling in cancer has been growing in popularity and impact since its inception in 1932. The first theoretical mathematical modeling in cancer research was focused on understanding tumor growth laws and has grown to include the competition between healthy and normal tissue, carcinogenesis, therapy and metastasis. It is the latter topic, metastasis, on which we will focus this short review, specifically discussing various computational and mathematical models of different portions of the metastatic process, including: the emergence of the metastatic phenotype, the timing and size distribution of metastases, the factors that influence the dormancy of micrometastases and patterns of spread from a given primary tumor.Comment: 24 pages, 6 figures, Revie

The Right’s Reasons: Constitutional Conflict and the Spread of Woman-Protective Anti-Abortion Argument

The Lecture offers a provisional first account of the rise and spread of WPAA. It traces the development of gender-based antiabortion advocacy, examining the rise of post-abortion syndrome (PAS) claims in the Reagan years and the first struggles in the antiabortion movement about whether the right to life is properly justified on the ground of women’s welfare. My story then follows changes in the abortion-harms-women claim, as it is transformed from PAS—a therapeutic and mobilizing discourse initially employed to dissuade women from having abortions and to recruit women to the antiabortion cause—into WPAA, a political discourse forged in the heat of movement conflict that seeks to persuade audiences outside the movement’s ranks in political campaigns and constitutional law. I tell a story in which social movement mobilization, coalition, and conflict each play a role in the evolution and spread of this constitutional argument, in the process forging new and distinctly modern ways to talk about the right to life and the role morality of motherhood in the therapeutic, public health, and political rights idiom of late twentieth-century America

The Notebook: An Accidental Alzheimer\u27s Awareness Campaign

My paper examines and critiques the portrayal of Alzheimer¹s disease in the popular film, The Notebook. Based off of a Nicholas Sparks novel, The Notebook uses Alzheimer¹s disease as a vehicle to relay a love story, but in doing so, presents a distorted picture of Alzheimer¹s disease to its audience. My paper compares the responsibilities of family caregivers of Alzheimer¹s patients in today¹s world with the unrealistic family caregiver, Noah, depicted on screen. My paper also explores and exposes inconsistencies between the attractive nursing home experience presented on screen and the less than ideal treatment patients experience in long term care facilities in America today. In addition, my paper uses several other films to examine and compare the emotional distress Alzheimer¹s disease patients and their families face when confronted with the condition: further underlining the idealized familial encounter with the disease depicted in The Notebook. My paper also examines the glamorized representation of Alzheimer¹s disease symptoms in the film. The misrepresentation and glamorization of Alzheimer¹s disease in The Notebook elicit serious implications in today¹s society. My paper describes how Alzheimer¹s awareness groups and other organizations utilize The Notebook as an educational tool to raise awareness for the condition, despite its imperfections. For better or worse, in today¹s society, people absorb a myriad of information from film and pop culture, leaving filmmakers with the difficult task of balancing entertainment and medicine in their films. Ultimately, my paper highlights this imbalance in The Notebook and describes its resulting accidental Alzheimer¹s awareness campaign

How to confuse with statistics or: the use and misuse of conditional probabilities

The article shows by various examples how consumers of statistical information may be confused when this information is presented in terms of conditional probabilities. It also shows how this confusion helps others to lie with statistics, and it suggests how either confusion or lies can be avoided by using alternative modes of conveying statistical information. --