Evaluation and accurate diagnoses of pediatric diseases using artificial intelligence

By Huiying Liang, B. Tsui, Hao Ni, C. Valentim, Sally L. Baxter, Guangjian Liu, Wenjia Cai, Daniel S. Kermany, Xin Sun, Jiancong Chen and 61 more. 2019

546 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Health Informatics, Radiology, Nuclear Medicine and Imaging

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Citations in the corpus

Improving the accuracy of medical diagnosis with causal machine learning (2020, methodology): “One approach to validating diagnostic algorithms is to use electronic health records (EHRs) 8 – 12 .”
Artificial intelligence in clinical and genomic diagnostics (2019, methodology): “When combined with genomic data, NLP-based methods have been used to predict rare disease diagnoses and to drive phenotype-informed genetic analysis, resulting in automated genetic diagnoses with accuracy similar to that of human experts [48, 49].”
Identification of COVID-19 can be quicker through artificial intelligence framework using a mobile phone–based survey when cities and towns are under quarantine (2020, unknown): “10, 11 Several studies have promoted disease detection through AI models.”
A transformer-based representation-learning model with unified processing of multimodal input for clinical diagnostics (2023, background): “Row HA (2) HA (0) HA (6) Unidirection Image ChiComp LabTest Tokenization Mean”
Key challenges for delivering clinical impact with artificial intelligence (2019, background): “…data collected from electronic health records (EHRs) offers promise in extracting clinically relevant information and making diagnostic evaluations [32] as well as in providing real-time risk scores for transfer to intensive care [33], predicting in-hospital mortality, readmission risk, prolonged…”
Artificial intelligence with multi-functional machine learning platform development for better healthcare and precision medicine (2020, background): “radiology (71) (early diagnosis, enhance visualization of pathologies and predicting emergency situations (64,73,71)), oncology (diagnosis of breast (75), skin (76), lung cancer (77)), cardiology (interpreting electrocardiogram readings, echocardiography with 3D cardiac imaging, cardiac CT angiograp”
A large language model for electronic health records (2022, background): “5,6 Nevertheless, free-text narratives cannot be easily used in computational models that usually require structured data.”