A riddle, wrapped in a mystery, inside an enigma:How semantic black boxes and opaque artificial intelligence confuse medical decision-making

The use of artificial intelligence (AI) in healthcare comes with opportunities but also numerous challenges. A specific challenge that remains underexplored is the lack of clear and distinct definitions of the concepts used in and/or produced by these algorithms, and how their real world meaning is translated into machine language and vice versa, how their output is understood by the end user. This "semantic" black box adds to the "mathematical" black box present in many AI systems in which the underlying "reasoning" process is often opaque. In this way, whereas it is often claimed that the use of AI in medical applications will deliver "objective" information, the true relevance or meaning to the end-user is frequently obscured. This is highly problematic as AI devices are used not only for diagnostic and decision support by healthcare professionals, but also can be used to deliver information to patients, for example to create visual aids for use in shared decision-making. This paper provides an examination of the range and extent of this problem and its implications, on the basis of cases from the field of intensive care nephrology. We explore how the problematic terminology used in human communication about the detection, diagnosis, treatment, and prognosis of concepts of intensive care nephrology becomes a much more complicated affair when deployed in the form of algorithmic automation, with implications extending throughout clinical care, affecting norms and practices long considered fundamental to good clinical care

A riddle, wrapped in a mystery, inside an enigma: How semantic black boxes and opaque artificial intelligence confuse medical decision-making

The use of artificial intelligence (AI) in healthcare comes with opportunities but also numerous challenges. A specific challenge that remains underexplored is the lack of clear and distinct definitions of the concepts used in and/or produced by these algorithms, and how their real world meaning is translated into machine language and vice versa, how their output is understood by the end user. This “semantic” black box adds to the “mathematical” black box present in many AI systems in which the underlying “reasoning” process is often opaque. In this way, whereas it is often claimed that the use of AI in medical applications will deliver “objective” information, the true relevance or meaning to the end-user is frequently obscured. This is highly problematic as AI devices are used not only for diagnostic and decision support by healthcare professionals, but also can be used to deliver information to patients, for example to create visual aids for use in shared decision-making. This paper provides an examination of the range and extent of this problem and its implications, on the basis of cases from the field of intensive care nephrology. We explore how the problematic terminology used in human communication about the detection, diagnosis, treatment, and prognosis of concepts of intensive care nephrology becomes a much more complicated affair when deployed in the form of algorithmic automation, with implications extending throughout clinical care, affecting norms and practices long considered fundamental to good clinical care

Establishing a Core Outcome Set for Autosomal Dominant Polycystic Kidney Disease: Report of the Standardized Outcomes in Nephrology–Polycystic Kidney Disease (SONG-PKD) Consensus Workshop

International audienceThe omission of outcomes that are of relevance to patients, clinicians, and regulators across trials in autosomal dominant polycystic kidney disease (ADPKD) limits shared decision making. The Standardized Outcomes in Nephrology-Polycystic Kidney Disease (SONG-PKD) Initiative convened an international consensus workshop on October 25, 2018, to discuss the identification and implementation of a potential core outcome set for all ADPKD trials. This article summarizes the discussion from the workshops and the SONG-PKD core outcome set. Key stakeholders including 11 patients/caregivers and 47 health professionals (nephrologists, policy makers, industry, and researchers) attended the workshop. Four themes emerged: "Relevance of trajectory and impact of kidney function" included concerns about a patient's prognosis and uncertainty of when they may need to commence kidney replacement therapy and the lack of an early prognostic marker to inform long-term decisions; "Discerning and defining pain specific to ADPKD" highlighted the challenges in determining the origin of pain, adapting to the chronicity and repeated episodes of pain, the need to place emphasis on pain management, and to have a validated measure for pain; "Highlighting ADPKD consequences" encompassed cyst-related complications and reflected patient's knowledge because of family history and the hereditary nature of ADPKD; and "Risk for life-threatening but rare consequences" such as cerebral aneurysm meant considering both frequency and severity of the outcome. Kidney function, mortality, cardiovascular disease, and pain were established as the core outcomes for ADPKD

CXCR4/CXCR7 Molecular Involvement in Neuronal and Neural Progenitor Migration: Focus in CNS Repair

In the adult brain, neural progenitor cells (NPCs) reside in the subventricular zone (SVZ) of the lateral ventricles, the dentate gyrus and the olfactory bulb. Following CNS insult, NPCs from the SVZ can migrate along the rostral migratory stream (RMS), a migration of NPCs that is directed by proinflammatory cytokines. Cells expressing CXCR4 follow a homing signal that ultimately leads to neuronal integration and CNS repair, although such molecules can also promote NPC quiescence. The ligand, SDF1 alpha (or CXCL12) is one of the chemokines secreted at sites of injury that it is known to attract NSC-derived neuroblasts, cells that express CXCR4. In function of its concentration, CXCL12 can induce different responses, promoting NPC migration at low concentrations while favoring cell adhesion via EGF and the alpha 6 integrin at high CXCL12 concentrations. However, the preclinical effectiveness of chemokines and their relationship with NPC mobilization requires further study, particularly with respect to CNS repair. NPC migration may also be affected by the release of cytokines or chemokines induced by local inflammation, through autocrine or paracrine mechanisms, as well as through erythropoietin (EPO) or nitric oxide (NO) release. CXCL12 activity requires G-coupled proteins and the availability of its ligand may be modulated by its binding to CXCR7, for which it shows a stronger affinity than for CXCR4