Using Artificial Intelligence in Fungal Lung Disease: CPA CT Imaging as an Example

Angelini, Elsa D.

doi:10.1007/s11046-021-00546-0

Cited by 9 publications

(4 citation statements)

References 33 publications

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“…57 AI has also been utilized in chronic pulmonary aspergillosis. 58 The application of imaging AI can be a unique opportunity that can help improve patient outcomes. 59 Table 1 depicts various studies using AI to diagnose and treat fungal infections.…”

Section: Ai In Fung Al Imag Ingmentioning

confidence: 99%

“…As a result, it helps pick up infection even in those who are usually not considered susceptible or risk group patients for a particular invasive fungal infection 57 . AI has also been utilized in chronic pulmonary aspergillosis 58 . The application of imaging AI can be a unique opportunity that can help improve patient outcomes 59 .…”

Section: Ai In Fungal Imagingmentioning

confidence: 99%

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Artificial Intelligence: Exploring utility in detection and typing of fungus with futuristic application in fungal cytology

Singla,

Kundu,

Dey

2023

Cytopathology

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Artificial Intelligence (AI) is an emerging, transforming and revolutionary technology that has captured attention worldwide. It is translating research into precision oncology treatments. AI can analyse large or big data sets requiring high‐speed specialized computing solutions. The data are big in terms of volume and multimodal with the amalgamation of images, text and structure. Machine learning has identified antifungal drug targets, and taxonomic and phylogenetic classification of fungi based on sequence analysis is now available. Real‐time identification tools and user‐friendly mobile applications for identifying fungi have been discovered. Akin to histopathology, AI can be applied to fungal cytology. AI has been fruitful in cytopathology of the thyroid gland, breast, urine and uterine cervical lesions. AI has a huge scope in fungal cytology and would certainly bear fruit with its accuracy, reproducibility and capacity for handling big data. The purpose of this systematic review was to highlight the AI's utility in detecting fungus and its typing with a special focus on future application in fungal cytology. We also touch upon the basics of AI in brief.

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Section: Ai In Fung Al Imag Ingmentioning

confidence: 99%

Section: Ai In Fungal Imagingmentioning

confidence: 99%

Artificial Intelligence: Exploring utility in detection and typing of fungus with futuristic application in fungal cytology

Singla,

Kundu,

Dey

2023

Cytopathology

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“…Advances in radiological technology have great potential to improve the diagnosis of IFRI. Artificial-intelligence (AI) could be developed to assist chest CT interpretation [70 ▪ ]. ‘Coarsening’ radiology reports using an optimised AI algorithm could help reduce unnecessary antifungal use [71].…”

Section: Future Directionsmentioning

confidence: 99%

Diagnosis of invasive respiratory mycoses in the immunocompromised host

Houston

Wilson

Stone

2023

Current Opinion in Pulmonary Medicine

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Purpose of reviewThe burden of invasive fungal infection is increasing worldwide, largely due to a growing population at-risk. Most serious human fungal pathogens enter the host via the respiratory tract. Early identification and treatment of invasive fungal respiratory infections (IFRIs) in the immunocompromised host saves lives. However, their accurate diagnosis is a difficult challenge for clinicians and mortality remains high.Recent findingsThis article reviews IFRIs, focussing on host susceptibility factors, clinical presentation, and mycological diagnosis. Several new diagnostic tools are coming of age including molecular diagnostics and point-of-care antigen tests. As diagnosis of IFRI relies heavily on invasive procedures like bronchoalveolar lavage and lung biopsy, several novel noninvasive diagnostic techniques are in development, such as metagenomics, ‘volatilomics’ and advanced imaging technologies.SummaryWhere IFRI cannot be proven, clinicians must employ a ‘weights-of-evidence’ approach to evaluate host factors, clinical and mycological data. Implementation studies are needed to understand how new diagnostic tools can be best applied within clinical pathways. Differentiating invasive infection from colonization and identifying antifungal resistance remain key challenges. As our diagnostic arsenal expands, centralized clinical mycology laboratories and efforts to ensure access to new diagnostics in low-resource settings will become increasingly important.

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“…The use of this technology has increased sharply when viewed from the use of the last few years. Where all regions really need the use of technology in the continuity of learning (Banja et al, 2022;Nagy et al, 2022;Thurzo et al, 2022), of course this is strongly associated with the role of the share of disease outbreaks that attack the world (Angelini & Shah, 2021;Bélisle-Pipon et al, 2021;N. Liu et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence as a Support for Arabic Language Learning in Higher Education with VOSviewer Analysis

Morales,

Lopez,

Joanan

et al. 2023

J. Journal International Inspire Education Technology

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The world is increasingly showing the progress of human resources in the field of science and technology, and the development of knowledge about this technology also continues to accelerate rapidly with the discovery of many features that have sprung up to be utilized according to human technological needs. Especially in the field of education, the development of technology-based features is also increasing, supported by technology-based learning systems. Newly emerging learning systems, such as an online machine-based intelligence apk that performs class teaching movements according to the connection provided by humans, this effort is a type of association in the interaction between robots and humans with correspondences that are linked between signals and movements. In this case, the robot provides an educational learning system with a discourse recognition process. The use of robots in learning Arabic in higher education also shows how an educational institution designs the latest technology-based learning system with the use of online robots to assist the learning process in the classroom. This online robot learning system is closely related to the use of supporting wireless network cables in the online robot association; therefore, a bibliometric analysis will be carried out on the use of artificial intelligence in supporting Arabic language learning in higher education with the help of VOSviewer. The results of the VOSviewer overview will provide conclusions about the extent to which artificial intelligence effectively supports Arabic language learning in higher education.

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Using Artificial Intelligence in Fungal Lung Disease: CPA CT Imaging as an Example

Cited by 9 publications

References 33 publications

Artificial Intelligence: Exploring utility in detection and typing of fungus with futuristic application in fungal cytology

Artificial Intelligence: Exploring utility in detection and typing of fungus with futuristic application in fungal cytology

Diagnosis of invasive respiratory mycoses in the immunocompromised host

Artificial Intelligence as a Support for Arabic Language Learning in Higher Education with VOSviewer Analysis

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