Abstract：
OBJECTIVE:This paper identifies and reviews ethical issues associated with artificial intelligent care providers (AICPs) in mental health care and other helping professions. Specific recommendations are made for the development of ethical codes, guidelines, and the design of AICPs. METHODS:Current developments in the application of AICPs and associated technologies are reviewed and a foundational overview of applicable ethical principles in mental health care is provided. Emerging ethical issues regarding the use of AICPs are then reviewed in detail. Recommendations for ethical codes and guidelines as well as for the development of semi-autonomous and autonomous AICP systems are described. The benefits of AICPs and implications for the helping professions are discussed in order to weigh the pros and cons of their use. RESULTS:Existing ethics codes and practice guidelines do not presently consider the current or the future use of interactive artificial intelligent agents to assist and to potentially replace mental health care professionals. AICPs present new ethical issues that will have significant ramifications for the mental health care and other helping professions. Primary issues involve the therapeutic relationship, competence, liability, trust, privacy, and patient safety. Many of the same ethical and philosophical considerations are applicable to use and design of AICPs in medicine, nursing, social work, education, and ministry. CONCLUSION:The ethical and moral aspects regarding the use of AICP systems must be well thought-out today as this will help to guide the use and development of these systems in the future. Topics presented are relevant to end users, AI developers, and researchers, as well as policy makers and regulatory boards.
journal_name
Artif Intell Medjournal_title
Artificial intelligence in medicineauthors
Luxton DDdoi
10.1016/j.artmed.2014.06.004subject
Has Abstractpub_date
2014-09-01 00:00:00pages
1-10issue
1eissn
0933-3657issn
1873-2860pii
S0933-3657(14)00068-2journal_volume
62pub_type
杂志文章abstract：OBJECTIVES:We propose a new graphical framework for extracting the relevant dietary, social and environmental risk factors that are associated with an increased risk of nasopharyngeal carcinoma (NPC) on a case-control epidemiologic study that consists of 1289 subjects and 150 risk factors. METHODS:This framework build...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2011.09.002
更新日期：2012-01-01 00:00:00
abstract：:As part of a plan to promote semi-automatic knowledge acquisition for the medical consultant system CADIAG-II/RHEUMA, this study sought to explore and cope with the variability of results that may be anticipated when performing knowledge acquisition with patient data from different patient settings. Patient data were ...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/s0933-3657(02)00025-8
更新日期：2002-07-01 00:00:00
abstract：OBJECTIVE:We provide a survey of recent advances in biomedical image analysis and classification from emergent imaging modalities such as terahertz (THz) pulse imaging (TPI) and dynamic contrast-enhanced magnetic resonance images (DCE-MRIs) and identification of their underlining commonalities. METHODS:Both time and f...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2016.01.005
更新日期：2016-02-01 00:00:00
abstract：BACKGROUND:The current situation of critical progression in resistance to more effective antibiotics has forced the reuse of old highly toxic antibiotics and, for several reasons, the extension of the indications of combined antibiotic therapy as alternative options to broad spectrum empirical mono-therapy. A key aspec...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2019.101751
更新日期：2020-01-01 00:00:00
abstract：AIM:A new automatic method for detecting specific points and lines (straight and curves) in dental panoramic radiographies (orthopantomographies) is proposed, where the human knowledge is mapped to the automatic system. The goal is to compute relevant mandibular indices (Mandibular Cortical Width, Panoramic Mandibular ...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2020.101816
更新日期：2020-03-01 00:00:00
abstract：OBJECTIVE:To use the detection of clinically relevant inconsistencies to support the reasoning capabilities of intelligent agents acting as physicians and tutors in the realm of clinical medicine. METHODS:We are developing a cognitive architecture, OntoAgent, that supports the creation and deployment of intelligent ag...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2012.04.005
更新日期：2012-07-01 00:00:00
abstract：:In this contribution we present an application of a knowledge-based neural network technique in the domain of medical research. We consider the crucial problem of intensive care patients developing a septic shock during their stay at the intensive care unit. Septic shock is of prime importance in intensive care medici...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/s0933-3657(03)00057-5
更新日期：2003-06-01 00:00:00
abstract：:This paper describes a methodology for achieving an efficient implementation of clinical practice guidelines. Three main steps are illustrated: knowledge representation, model simulation and implementation within a health care organisation. The resulting system can be classified as a 'guideline-based careflow manageme...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/s0933-3657(00)00050-6
更新日期：2000-08-01 00:00:00
abstract：BACKGROUND:Patients who are readmitted to an intensive care unit (ICU) usually have a high risk of mortality and an increased length of stay. ICU readmission risk prediction may help physicians to re-evaluate the patient's physical conditions before patients are discharged and avoid preventable readmissions. ICU readmi...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2018.08.004
更新日期：2019-04-01 00:00:00
abstract：:The automated analysis of retinal images is a widely researched area which can help to diagnose several diseases like diabetic retinopathy in early stages of the disease. More specifically, separation of vessels and lesions is very critical as features of these structures are directly related to the diagnosis and trea...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2019.07.010
更新日期：2019-08-01 00:00:00
abstract：:The advent of cardiovascular diseases as a disease of mass catastrophy, in recent years is alarming. It is expected to spread as an epidemic by 2030. Present methods of determining the health of one's heart include doppler based echocardiogram, MDCT (Multi Detector Computed Tomography), among various other invasive an...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2019.02.002
更新日期：2019-05-01 00:00:00
abstract：:Manual delineation of vestibular schwannoma (VS) by magnetic resonance (MR) imaging is required for diagnosis, radiosurgery dose planning, and follow-up tumor volume measurement. A rapid and objective automatic segmentation method is required, but problems have been encountered due to the low through-plane resolution ...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2020.101911
更新日期：2020-07-01 00:00:00
abstract：:The process of patient care performed by an anaesthesiologist during high invasive surgery requires fundamental knowledge of the physiologic processes and a long standing experience in patient management to cope with the inter-individual variability of the patients. Biomedical engineering research improves the patient...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/s0933-3657(97)00020-1
更新日期：1997-09-01 00:00:00
abstract：BACKGROUND:The Arden Syntax is a knowledge-encoding standard, started in 1989, and now in its 10th revision, maintained by the health level seven (HL7) organization. It has constructs borrowed from several language concepts that were available at that time (mainly the HELP hospital information system and the Regenstrie...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2015.11.003
更新日期：2018-11-01 00:00:00
abstract：:Diagnosis of visual function losses in glaucomatous patients depends to a large extent on the analysis of the data collected from corresponding psychophysical tests. One of the main difficulties in obtaining reliable data from patients in these tests is the measurement noise caused by the learning effect, inattention,...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/0933-3657(94)90004-3
更新日期：1994-10-01 00:00:00
abstract：OBJECTIVE:Formulate the induction and control of gene regulatory networks (GRNs) from gene expression data using Partially Observable Markov Decision Processes (POMDPs). METHODS AND MATERIAL:Different approaches exist to model GRNs; they are mostly simulated as mathematical models that represent relationships between ...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2017.06.007
更新日期：2017-11-01 00:00:00
abstract：OBJECTIVE:We address the task of inducing explanatory models from observations and knowledge about candidate biological processes, using the illustrative problem of modeling photosynthesis regulation. METHODS:We cast both models and background knowledge in terms of processes that interact to account for behavior. We a...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2006.04.003
更新日期：2006-07-01 00:00:00
abstract：BACKGROUND:Motor vehicle accidents (MVA) represent a significant burden on health systems globally. Tens of thousands of people are injured in Australia every year and may experience significant disability. Associated economic costs are substantial. There is little literature on the health service utilization patterns ...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2020.101997
更新日期：2021-01-01 00:00:00
abstract：OBJECTIVE:New medical systems may be rejected by staff because they do not integrate with local practice. An expert system, FLORENCE, is being developed to help staff in a neonatal intensive care unit (NICU) make decisions about ventilator settings when treating babies with respiratory distress syndrome. For FLORENCE t...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2005.01.004
更新日期：2005-11-01 00:00:00
abstract：OBJECTIVE:High dose radiation has been well known for increasing the risk of carcinogenesis. However, the understanding of biological effects of low dose radiation is limited. Low dose radiation is reported to affect several signaling pathways including deoxyribonucleic acid repair, survival, cell cycle, cell growth, a...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2010.04.001
更新日期：2010-07-01 00:00:00
abstract：:As a crucial step of biological event extraction, event trigger identification has attracted much attention in recent years. Deep representation methods, which have the superiorities of less feature engineering and end-to-end training, show better performance than statistical methods. While most deep learning methods ...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2019.101783
更新日期：2020-03-01 00:00:00
abstract：OBJECTIVE:The aim of this paper is to provide an improved method for solving the so-called dynamic patient admission scheduling (DPAS) problem. This is a complex scheduling problem that involves assigning a set of patients to hospital beds over a given time horizon in such a way that several quality measures reflecting...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2016.10.002
更新日期：2016-11-01 00:00:00
abstract：OBJECTIVE:We present a combined terminological resource for text mining over biomedical literature. The purpose of the resource is to allow the detection of mentions of specific biological entities in scientific publications, and their grounding to widely accepted identifiers. This is an essential process, useful in it...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2011.04.011
更新日期：2011-06-01 00:00:00
abstract：OBJECTIVE:A metaschema is an abstraction network of the UMLS's semantic network (SN) obtained from a connected partition of its collection of semantic types. A lexical metaschema was previously derived based on a lexical partition which partitioned the SN into semantic-type groups using identical word-usage among the n...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2005.01.002
更新日期：2005-07-01 00:00:00
abstract：BACKGROUND AND MOTIVATION:DNA microarray technology has made it possible to determine the expression levels of thousands of genes in parallel under multiple experimental conditions. Genome-wide analyses using DNA microarrays make a great contribution to the exploration of the dynamic state of genetic networks, and furt...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2005.02.007
更新日期：2005-09-01 00:00:00
abstract：OBJECTIVE:The objective of this work is to investigate a possibility of creating a computer-aided decision support system for an automated analysis of vocal cord images aiming to categorize diseases of vocal cords. METHODOLOGY:The problem is treated as a pattern recognition task. To obtain a concise and informative re...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2004.11.001
更新日期：2006-01-01 00:00:00
abstract：OBJECTIVE:Gene Ontology (GO) has become a routine resource for functional analysis of gene lists. Although a number of tools have been provided to identify enriched GO terms in one or two gene lists, two technical challenges remain. First, how to handle multiple hypothesis testing in the analysis given that the tests a...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2007.08.002
更新日期：2007-10-01 00:00:00
abstract：:In a digitally enabled healthcare setting, we posit that an individual's current location is pivotal for supporting many virtual care services-such as tailoring educational content towards an individual's current location, and, hence, current stage in an acute care process; improving activity recognition for supportin...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2020.101931
更新日期：2020-08-01 00:00:00
abstract：OBJECTIVE:In this paper a new nonlinear system identification approach is developed for dynamical quantification of cardiovascular regulation. This approach is specifically focused on the identification of the heart rate (HR) baroreflex mechanism. The principal objective of this paper is to improve the model accuracy i...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2011.01.002
更新日期：2011-05-01 00:00:00
abstract：OBJECTIVE:Two major problems related the unsupervised analysis of gene expression data are represented by the accuracy and reliability of the discovered clusters, and by the biological fact that the boundaries between classes of patients or classes of functionally related genes are sometimes not clearly defined. The ma...
journal_title：Artificial intelligence in medicine
pub_type： 杂志文章
doi：10.1016/j.artmed.2008.07.014
更新日期：2009-02-01 00:00:00
