ReviewFrontiers in medicine2025
Advancing clinical biochemistry: addressing gaps and driving future innovations.
Review in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Recent Progress in Artificial Intelligence in Biosensor Development: From Bioprobe Design to Fabrication and Signal Analysis.Biosensors · 2026Review
- From Biomarkers to Biosensors: Transforming Comorbidity Management in Dialysis Care.Sensors (Basel, Switzerland) · 2026Review
- Liquid biopsy epigenetics: establishing a molecular profile based on cell-free DNA.Molecular oncology · 2026Review
- Daily SPARK-A Comic Style eMicrolearning to Enhance Clinical Reasoning and Reinforce Conceptual Understanding in Biochemistry Promoting Its Application to Clinical Practice.Biochemistry and molecular biology education : a bimonthly publication of the International Union of Biochemistry and Molecular BiologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Modern healthcare depends fundamentally on clinical biochemistry for disease diagnosis and therapeutic guidance. The discipline encounters operational constraints, including sampling inefficiencies, precision limitations, and expansion difficulties. Recent advancements in established technologies, such as mass spectrometry and the development of high-throughput screening and point-of-care technologies, are revolutionizing the industry. Modern biosensor technology and wearable monitors facilitate continuous health tracking, Artificial Intelligence (AI)/machine learning (ML) applications enhance analytical capabilities, generating predictive insights for individualized treatment protocols. However, concerns regarding algorithmic bias, data privacy, lack of transparency in decision-making ("black box" models), and over-reliance on automated systems pose significant challenges that must be addressed for responsible AI integration. However, significant limitations remain-substantial implementation expenses, system incompatibility issues, and information security vulnerabilities intersect with ethical considerations regarding algorithmic fairness and protected health information. Addressing these challenges demands coordinated efforts between clinicians, scientists, and technical specialists. This review discusses current challenges in clinical biochemistry, explicitly addressing the limitations of reference intervals and barriers to implementing innovative biomarkers in medical settings. The discussion evaluates how advanced technologies and multidisciplinary collaboration can overcome these constraints while identifying research priorities to enhance diagnostic precision and accessibility for better healthcare delivery.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.