{"doi":"10.1515/cclm-2023-1408","title":"Considerations for applying emerging technologies in paediatric laboratory medicine","abstract":"<jats:title>Abstract</jats:title>\n               <jats:p>Emerging technology in laboratory medicine can be defined as an analytical method (including biomarkers) or device (software, applications, and algorithms) that by its stage of development, translation into broad routine clinical practice, or geographical adoption and implementation has the potential to add value to clinical diagnostics. Paediatric laboratory medicine itself may be considered an emerging area of specialisation that is established relatively recently following increased appreciation and understanding of the unique physiology and healthcare needs of the children. Through four clinical (neonatal hypoglycaemia, neonatal hyperbilirubinaemia, sickle cell disorder, congenital adrenal hyperplasia) and six technological (microassays, noninvasive testing, alternative matrices, next generation sequencing, exosome analysis, machine learning) illustrations, key takeaways of application of emerging technology for each area are summarised. Additionally, nine key considerations when applying emerging technology in paediatric laboratory medicine setting are discussed.</jats:p>","journal":"Clinical Chemistry and Laboratory Medicine (CCLM)","year":2024,"id":623779,"datarank":0.31506257479960925,"base_score":1.6094379124341003,"endowment":1.6094379124341003,"self_citation_contribution":0.24141568686511508,"citation_network_contribution":0.07364688793449418,"self_endowment_contribution":0.24141568686511508,"citer_contribution":0.07364688793449418,"corpus_percentile":null,"corpus_rank":null,"citation_count":4,"citer_count":4,"citers_with_citation_signal":1,"citers_with_endowment":1,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1612266,"name":"Sharon Geaghan","orcid":null,"position":1,"is_corresponding":false},{"id":1612267,"name":"Tze Ping Loh","orcid":null,"position":2,"is_corresponding":false},{"id":938303,"name":"Chloe Miu Mak","orcid":"0000-0003-1419-489X","position":3,"is_corresponding":false},{"id":1612269,"name":"Ioannis Papassotiriou","orcid":"0000-0002-2126-3251","position":4,"is_corresponding":false},{"id":1612270,"name":"Lianna G. Kyriakopoulou","orcid":null,"position":5,"is_corresponding":false},{"id":1612265,"name":"Tim Lang","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Considerations for applying emerging technologies in paediatric laboratory medicine","abstract":"<jats:title>Abstract</jats:title>\n               <jats:p>Emerging technology in laboratory medicine can be defined as an analytical method (including biomarkers) or device (software, applications, and algorithms) that by its stage of development, translation into broad routine clinical practice, or geographical adoption and implementation has the potential to add value to clinical diagnostics. Paediatric laboratory medicine itself may be considered an emerging area of specialisation that is established relatively recently following increased appreciation and understanding of the unique physiology and healthcare needs of the children. Through four clinical (neonatal hypoglycaemia, neonatal hyperbilirubinaemia, sickle cell disorder, congenital adrenal hyperplasia) and six technological (microassays, noninvasive testing, alternative matrices, next generation sequencing, exosome analysis, machine learning) illustrations, key takeaways of application of emerging technology for each area are summarised. Additionally, nine key considerations when applying emerging technology in paediatric laboratory medicine setting are discussed.</jats:p>","is_dataset_classified":null,"base_score":1.6094379124341003,"endowment":1.6094379124341003,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"39044644","pmcid":null,"openalex_id":"https://openalex.org/W4400916404","authors":[],"funders":[],"total_grants":0,"fwci":1.5984,"citation_percentile":0.83753338,"influential_citations":0,"citation_trend":[{"year":2024,"count":1},{"year":2025,"count":2},{"year":2026,"count":1}],"oa_status":"closed","license":null,"oa_locations":[{"url":"https://www.degruyter.com/document/doi/10.1515/cclm-2023-1408/xml","host_type":"publisher"},{"url":"https://www.degruyter.com/document/doi/10.1515/cclm-2023-1408/pdf","host_type":"publisher"},{"url":"https://doi.org/10.1515/cclm-2023-1408","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/39044644","host_type":"repository"}],"fields_of_study":["Blood disorders and treatments","Blood groups and transfusion","Hyperglycemia and glycemic control in critically ill and hospitalized patients","Humans","Pediatrics","Child","Infant, Newborn","High-Throughput Nucleotide Sequencing","Adrenal Hyperplasia, Congenital","Anemia, Sickle Cell","Biomarkers","Hyperbilirubinemia, Neonatal","Machine Learning","Clinical Laboratory Techniques"],"mesh_terms":["Machine Learning","Adrenal Hyperplasia, Congenital","Anemia, Sickle Cell","Child","Humans","Infant, Newborn","Pediatrics","Biomarkers","Clinical Laboratory Techniques","Hyperbilirubinemia, Neonatal","High-Throughput Nucleotide Sequencing"],"keywords":["Emerging technologies","Congenital adrenal hyperplasia","Medicine","Clinical Practice","Health technology","Medical laboratory","Medical physics","Health care","Intensive care medicine","Computer science","Data science","Pathology","Artificial intelligence","Internal medicine","Family medicine","Screening","Newborn","Diagnostics","Emerging Technology","Paediatric Laboratory Medicine"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Industry, innovation and infrastructure"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-04T01:19:29.275845Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}