Intuitive decision making

MOTIVATION: ITree is an intuitive web tool for the manual, semi-automatic, and automatic induction of decision trees. It enables interactive modifications of tree structures and incorporates Relative Expression Analysis for detecting complex patterns in high-throughput molecular data. This makes ITree a versatile tool for both research and education in biomedical data analysis. RESULTS: The tool allows users to instantly see the effects of modifications on decision trees, with updates to predictions and statistics displayed in real time, facilitating a deeper understanding of data classification processes...

Despite evidence that elite-level cricket umpires are highly accurate in making leg-before-wicket (LBW) judgements, there is limited understanding as to how they make these judgements. In this study, we explored the explicit LBW decision-making expertise of elite-level cricket umpires ( N  = 10) via 10 individual semi-structured interviews. Using thematic analysis, we aimed to identify the sources of information that umpires incorporate into their decision-making process. Results indicated that umpires engage in intentional pre-delivery information-gathering to guide their expectations, and to set context-specific parameters as to what would constitute an LBW dismissal...

Model-based tumor growth inhibition (TGI) metrics are increasingly used to predict overall survival (OS) data in Phase III immunotherapy clinical trials. However, there is still a lack of understanding regarding the differences between two-stage or joint modeling methods to leverage Phase I/II trial data and help early decision-making. A recent study showed that TGI metrics such as the tumor growth rate constant KG may have good operating characteristics as early endpoints. This previous study used a two-stage approach that is easy to implement and intuitive but prone to bias as it does not account for the relationship between the longitudinal and time-to-event processes...

People frequently face decisions that require making inferences about withheld information. The advent of large language models coupled with conversational technology, e.g., Alexa, Siri, Cortana, and the Google Assistant, is changing the mode in which people make these inferences. We demonstrate that conversational modes of information provision, relative to traditional digital media, result in more critical responses to withheld information, including: (1) a reduction in evaluations of a product or service for which information is withheld and (2) an increased likelihood of recalling that information was withheld...

OBJECTIVES: The elimination of mother-to-child transmission (MTCT) of syphilis has been set as a public health priority. However, an instrument to predict the MTCT of syphilis is not available. We aimed to develop and validate an intuitive nomogram to predict the individualised risk of MTCT in pregnant women with syphilis in China. DESIGN: Retrospective cohort study. SETTING: Data was acquired from the National Information System of Prevention of MTCT of Syphilis in Guangdong province between 2011 and 2020...

Expanding and managing current habitat and species protection measures is at the heart of the European biodiversity strategy. A structured approach is needed to gain insights into such issues is systematic conservation planning, which uses techniques from decision theory to identify places and actions that contribute most effectively to policy objectives given a set of constraints. Yet culturally and historically determined European landscapes make the implementation of any conservation plans challenging, requiring an analysis of synergies and trade-offs before implementation...

OBJECTIVES: This study aims to qualitatively examine nurses' perception of uncertainty regarding suspected pain in people with dementia (PWD). DESIGN: The study utilized a qualitative descriptive design. PARTICIPANTS: The participants in this study were nurses with a minimum of six months of experience caring for PWD and currently working in a university hospital in Irbid, Jordan. Twenty-five participants were selected using convenience sampling from the selected hospital...

Suicide is a complex, multidimensional event, and a significant challenge for prevention globally. Artificial intelligence (AI) and machine learning (ML) have emerged to harness large-scale datasets to enhance risk detection. In order to trust and act upon the predictions made with ML, more intuitive user interfaces must be validated. Thus, Interpretable AI is one of the crucial directions which could allow policy and decision makers to make reasonable and data-driven decisions that can ultimately lead to better mental health services planning and suicide prevention...

The nursing shortage that is upon us is the result of a confluence of factors, some simple and some complex. Legacy solutions are not working. Recovery from the current situation involves examining and reshaping the nursing work environment. Creative and innovative solutions are being developed and tested. The call for addressing the work environment is surfacing in the literature, yet methods for doing so in an orderly, progressive manner have been elusive. To solve complex problems, structure helps lead to clear thinking...

INTRODUCTION: Consensus over the definition of recombinant factor VIII (rFVIII) product classification in haemophilia A is lacking. rFVIII products are often classified as standard half-life (SHL) or extended half-life (EHL); despite this, no universally accepted definition currently exists. One proposed definition includes half-life, area under the curve, and technology designed to extend half-life; however, the International Society on Thrombosis and Haemostasis defines activity over time as the most intuitive information for building treatment regimens and the World Federation of Hemophilia describes rFVIII product classification in terms of infusion frequency...

The effect of demand uncertainty reduction (DUR) on supply chain management has received tremendous attention. From a financial perspective, studying the impact of DUR is equally significant. This study explores the relationship between DUR and private equity (PE) financing in retail enterprises within a supply chain, which comprises a dominant supplier and a subordinate retailer. This article establishes decision models for a retailer backed by PE under three market demand conditions: range, mean, and range with mean...

Weaning patients from mechanical ventilation (MV) is a critical and resource intensive process in the Intensive Care Unit (ICU) that impacts patient outcomes and healthcare expenses. Weaning methods vary widely among providers. Prolonged MV is associated with adverse events and higher healthcare expenses. Predicting weaning readiness is a non-trivial process in which the positive end-expiratory pressure (PEEP), a crucial component of MV, has potential to be indicative but has not yet been used as the target...

Autonomous driving is no more a topic of science fiction. Advancement of autonomous driving technologies are now reliable. Effectively harnessing the information is essential for enhancing the safety, reliability, and efficiency of autonomous vehicles. In this article, we explore the pivotal role of visualization and visual analytics (VA) techniques used in autonomous driving. By employing sophisticated data visualization methods, VA, researchers and practitioners transform intricate datasets into intuitive visual representations, providing valuable insights for decision-making processes...

BACKGROUND: The safety of telemedicine in general and telephone triage (teletriage) safety in particular have been a focus of concern since the 1970s. Today, telehealth, now subsuming teletriage, has a basic structure and process intended to promote safety. However, inadequate telehealth systems may also compromise patient safety. The COVID-19 pandemic accelerated rapid but uneven telehealth growth, both technologically and professionally. Within 5-10 years, the field will likely be more technologically advanced; however, these advances may still outpace professional standards...

In today's digital era, the rapid growth of databases presents significant challenges in data management. In order to address this, we have developed and designed CHAMP (Cervical Health Assessment using machine learning for Prediction), which is a user interface tool that can effectively and efficiently handle cervical cancer databases to detect patterns for future prediction diagnosis. CHAMP employs various machine learning algorithms which include XGBoost, SVM, Naive Bayes, AdaBoost, Decision Tree, and K-Nearest Neighbors in order to predict cervical cancer accurately...

In the realm of law enforcement, the "police hunch" has long been a mysterious but crucial aspect of decision-making. Drawing on the developing framework of Active Inference from cognitive science, this theoretical article examines the genesis, mechanics, and implications of the police hunch. It argues that hunches - often vital in high-stakes situations - should not be described as mere intuitions, but as intricate products of our mind's generative models. These models, shaped by observations of the social world and assimilated and enacted through active inference, seek to reduce surprise and make hunches an indispensable tool for officers, in exactly the same way that hypotheses are indispensable for scientists...

COVID-19 caused an imbalance between medical resources and the number of patients in Türkiye like in many countries. There was not pandemic-triage system, and this situation led to decision making based on experience, intuition, and judgment of allocation of scarce resources. The research explains the guiding criteria that healthcare professionals used to prioritize the distribution of scarce medical resources during the COVID-19 pandemic. The criteria preferred by 928 healthcare professionals were evaluated when preventive measures for COVID-19 were reduced and so the number of cases increased rapidly...

In order to efficiently divide labor with others, it is important to understand what our collaborators can do (i.e., their competence). However, competence is not static-people get better at particular jobs the more often they perform them. This plasticity of competence creates a challenge for collaboration: For example, is it better to assign tasks to whoever is most competent now, or to the person who can be trained most efficiently "on-the-job"? We conducted four experiments (N=396) that examine how people make decisions about whom to train (Experiments 1 and 3) and whom to recruit (Experiments 2 and 4) to a collaborative task, based on the simulated collaborators' starting expertise, the training opportunities available, and the goal of the task...

Unverified or false information spread by irresponsible users can amplify the dissemination of fake news or misinformation. This phenomenon may not only undermine the credibility of social media platforms but also pose severe consequences for individuals and society. This study applies and extends the prototypical willingness model with the aim of comprehending the reasons, and decision-making process driving users' unverified information-sharing behavior a reasoned and intended pathway or an impulsive and unconscious one...

Some research has shown that expectations modulate people's economic dishonesty. These studies have allowed their participants to precisely establish the dishonest extra financial gain, without threatening their image of honesty. In this article, we show that in situations where our economic dishonesty is driven by hard-to-quantify motivators such as level of effort, it is difficult to change the categorization of (dishonest) judgments. Faced with this ambiguity, people make decisions guided by moral intuitions that are not conditioned by changing expectations...