Result 1 - 10 of total 2938
Western journal of medicine and surgery
2024 Volume 9, Issue 3, Page(s) 258–260
| Language | English |
|---|---|
| Publishing date | 2024-01-11 |
| Publishing country | United States |
| Document type | Journal Article |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.
The Homoeopathic physician
2023 Volume 8, Issue 8, Page(s) 422–423
| Language | English |
|---|---|
| Publishing date | 2023-05-01 |
| Publishing country | United States |
| Document type | Journal Article |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.
British journal of nursing (Mark Allen Publishing)
2023 Volume 32, Issue 22, Page(s) 1092–1097
Abstract: Waterless bathing techniques can enhance the care of patients with neurological difficulties. Traditional methods can be uncomfortable and time consuming. Hospital-acquired infections in the NHS are a significant concern because of both financial burdens ...
| Abstract | Waterless bathing techniques can enhance the care of patients with neurological difficulties. Traditional methods can be uncomfortable and time consuming. Hospital-acquired infections in the NHS are a significant concern because of both financial burdens and antibiotic resistance, and preventing them is paramount. Conti |
|---|---|
| MeSH term(s) | Humans ; Anti-Infective Agents, Local ; Chlorhexidine ; Inpatients ; Cross Infection/prevention & control ; Baths/methods |
| Chemical Substances | Anti-Infective Agents, Local ; Chlorhexidine (R4KO0DY52L) |
| Language | English |
| Publishing date | 2023-12-14 |
| Publishing country | England |
| Document type | Journal Article |
| ZDB-ID | 1119191-0 |
| ISSN | 0966-0461 |
| ISSN | 0966-0461 |
| DOI | 10.12968/bjon.2023.32.22.1092 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
| Zs.A 3449: Show issues | Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (2.OG) ab Jg. 2022: Lesesaal (EG) |
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2024
| Language | English |
|---|---|
| Publishing date | 2024-04-24 |
| Publishing country | United States |
| Document type | Journal Article |
| ZDB-ID | 2701841-6 |
| ISSN | 2168-6262 ; 2168-6254 |
| ISSN (online) | 2168-6262 |
| ISSN | 2168-6254 |
| DOI | 10.1001/jamasurg.2024.0752 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
| Uk I Zs.72: Show issues | Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular ab Jg. 2022: Lesesaal (EG) |
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NPJ digital medicine
2024 Volume 7, Issue 1, Page(s) 89
Abstract: An increasing number of artificial intelligence (AI) tools are moving towards the clinical realm in histopathology and across medicine. The introduction of such tools will bring several benefits to diagnostic specialities, namely increased diagnostic ... ...
| Abstract | An increasing number of artificial intelligence (AI) tools are moving towards the clinical realm in histopathology and across medicine. The introduction of such tools will bring several benefits to diagnostic specialities, namely increased diagnostic accuracy and efficiency, however, as no AI tool is infallible, their use will inevitably introduce novel errors. These errors made by AI tools are, most fundamentally, misclassifications made by a computational algorithm. Understanding of how these translate into clinical impact on patients is often lacking, meaning true reporting of AI tool safety is incomplete. In this Perspective we consider AI diagnostic tools in histopathology, which are predominantly assessed in terms of technical performance metrics such as sensitivity, specificity and area under the receiver operating characteristic curve. Although these metrics are essential and allow tool comparison, they alone give an incomplete picture of how an AI tool's errors could impact a patient's diagnosis, management and prognosis. We instead suggest assessing and reporting AI tool errors from a pathological and clinical stance, demonstrating how this is done in studies on human pathologist errors, and giving examples where available from pathology and radiology. Although this seems a significant task, we discuss ways to move towards this approach in terms of study design, guidelines and regulation. This Perspective seeks to initiate broader consideration of the assessment of AI tool errors in histopathology and across diagnostic specialities, in an attempt to keep patient safety at the forefront of AI tool development and facilitate safe clinical deployment. |
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| Language | English |
| Publishing date | 2024-04-10 |
| Publishing country | England |
| Document type | Journal Article ; Review |
| ISSN | 2398-6352 |
| ISSN (online) | 2398-6352 |
| DOI | 10.1038/s41746-024-01093-w |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.
Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.
The Dental register
2021 Volume 24, Issue 12, Page(s) 541
| Language | English |
|---|---|
| Publishing date | 2021-03-10 |
| Publishing country | United States |
| Document type | Journal Article |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.
2023 Volume 84, Issue 2, Page(s) 279–287
Abstract: Artificial intelligence (AI)-based diagnostic tools can offer numerous benefits to the field of histopathology, including improved diagnostic accuracy, efficiency and productivity. As a result, such tools are likely to have an increasing role in routine ... ...
| Abstract | Artificial intelligence (AI)-based diagnostic tools can offer numerous benefits to the field of histopathology, including improved diagnostic accuracy, efficiency and productivity. As a result, such tools are likely to have an increasing role in routine practice. However, all AI tools are prone to errors, and these AI-associated errors have been identified as a major risk in the introduction of AI into healthcare. The errors made by AI tools are different, in terms of both cause and nature, to the errors made by human pathologists. As highlighted by the National Institute for Health and Care Excellence, it is imperative that practising pathologists understand the potential limitations of AI tools, including the errors made. Pathologists are in a unique position to be gatekeepers of AI tool use, maximizing patient benefit while minimizing harm. Furthermore, their pathological knowledge is essential to understanding when, and why, errors have occurred and so to developing safer future algorithms. This paper summarises the literature on errors made by AI diagnostic tools in histopathology. These include erroneous errors, data concerns (data bias, hidden stratification, data imbalances, distributional shift, and lack of generalisability), reinforcement of outdated practices, unsafe failure mode, automation bias, and insensitivity to impact. Methods to reduce errors in both tool design and clinical use are discussed, and the practical roles for pathologists in error minimisation are highlighted. This aims to inform and empower pathologists to move safely through this seismic change in practice and help ensure that novel AI tools are adopted safely. |
|---|---|
| MeSH term(s) | Humans ; Artificial Intelligence ; Pathologists ; Algorithms |
| Language | English |
| Publishing date | 2023-11-03 |
| Publishing country | England |
| Document type | Journal Article |
| ZDB-ID | 131914-0 |
| ISSN | 1365-2559 ; 0309-0167 |
| ISSN (online) | 1365-2559 |
| ISSN | 0309-0167 |
| DOI | 10.1111/his.15071 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
| Zs.A 1328: Show issues | Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (1.OG) ab Jg. 2022: Lesesaal (EG) |
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2023 Volume 151, Issue 2
| MeSH term(s) | Humans ; History, 20th Century ; Pandemics ; Child, Orphaned ; Influenza Pandemic, 1918-1919 ; Influenza, Human/epidemiology |
|---|---|
| Language | English |
| Publishing date | 2023-01-01 |
| Publishing country | United States |
| Document type | Historical Article ; Journal Article |
| ZDB-ID | 207677-9 |
| ISSN | 1098-4275 ; 0031-4005 |
| ISSN (online) | 1098-4275 |
| ISSN | 0031-4005 |
| DOI | 10.1542/peds.2021-054525 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
| Um IV Zs.131: Show issues | Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular ab Jg. 2022: Lesesaal (EG) |
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| Zs.MO 357: Show issues |
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2018 Volume 126, Issue 6492, Page(s) 16–17
Abstract: The benefits to the public of sharing their health data must be articulated more compellingly if their trust is to be won. ...
| Abstract | The benefits to the public of sharing their health data must be articulated more compellingly if their trust is to be won. |
|---|---|
| MeSH term(s) | Delivery of Health Care ; Information Dissemination ; Medical Informatics ; State Medicine ; Systems Integration ; United Kingdom |
| Language | English |
| Publishing date | 2018-09-01 |
| Publishing country | England |
| Document type | Journal Article |
| ZDB-ID | 632799-0 |
| ISSN | 0952-2271 ; 0300-8347 |
| ISSN | 0952-2271 ; 0300-8347 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
| Zs.B 1112: Show issues | Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular ab Jg. 2022: Lesesaal (EG) |
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IUCrData
2022 Volume 7, Issue Pt 2, Page(s) x220077
Abstract: The reaction of ... ...
| Abstract | The reaction of AgNO |
|---|---|
| Language | English |
| Publishing date | 2022-02-01 |
| Publishing country | England |
| Document type | Journal Article |
| ISSN | 2414-3146 |
| ISSN (online) | 2414-3146 |
| DOI | 10.1107/S2414314622000773 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.
Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.