AIMC Topic: Hemoglobins

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Hemoglobin-based oxygen carriers promote systemic hyperfibrinolysis that is both dependent and independent of plasmin.

The Journal of surgical research
BACKGROUND: Hyperfibrinolysis plays an integral role in the genesis of trauma-induced coagulopathy. Recent data demonstrate that red blood cell lysis promotes fibrinolysis; however, the mechanism is unclear. Hemoglobin-based oxygen carriers (HBOCs) h...

Variational mode decomposition unfolded extreme learning machine for spectral quantitative analysis of complex samples.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Considering the advantages of variational mode decomposition (VMD) in mathematical decomposition and extreme learning machine (ELM) in data modeling, a new regression model named variational mode decomposition unfolded extreme learning machine (VMD-U...

Can polycythaemia vera disease be predicted from haematologic parameters? A machine learning-based study.

Journal of clinical pathology
AIMS: The aim of this research is to diagnose polycythaemia vera (PV) disease using different machine learning (ML) algorithms with complete blood count (CBC) parameters before further investigations such as Janus kinase 2 (), erythropoietin (EPO) an...

Deciphering the molecular fingerprint of haemoglobin in lung cancer: A new strategy for early diagnosis using two-trace two-dimensional correlation near infrared spectroscopy (2T2D-NIRS) and machine learning techniques.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Lung cancer remains one of the deadliest malignancies worldwide, highlighting the need for highly sensitive and minimally invasive early diagnostic methods. Near-infrared spectroscopy (NIRS) offers unique advantages in probing molecular vibrational i...

Machine-learning models to predict iron recovery after blood donation: a model development and external validation study.

The Lancet. Haematology
BACKGROUND: Machine-learning models directly predicting iron biomarkers after blood donation could help to manage donation-associated iron deficiency and avoid low haemoglobin deferrals. No such models have been externally validated internationally. ...

[Rapid identification and analysis of hemoglobin isoelectric focusing electrophoresis images based on deep learning].

Se pu = Chinese journal of chromatography
Gel electrophoresis is used to separate and analyze macromolecules (such as DNA, RNA, and proteins) and their fragments, and highly reproducible and efficient automatic band-detection methods have been developed to analyze gel images. Uneven backgrou...

Machine learning of blood haemoglobin and haematocrit levels via smartphone conjunctiva photography in Kenyan pregnant women: a clinical study protocol.

BMJ open
INTRODUCTION: Anaemia during pregnancy is a widespread health burden globally, especially in low- and middle-income countries, posing a serious risk to both maternal and neonatal health. The primary challenge is that anaemia is frequently undetected ...

[Serum proteomics and machine learning unveil new diagnostic biomarkers for tuberculosis in adolescents and young adults].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology
Adolescents and young adults (AYAs) are one of the major populations susceptible to tuberculosis. However, little is known about the unique characteristics and diagnostic biomarkers of tuberculosis in this population. In this study, 81 AYAs were recr...

Noninvasive Anemia Detection and Hemoglobin Estimation from Retinal Images Using Deep Learning: A Scalable Solution for Resource-Limited Settings.

Translational vision science & technology
PURPOSE: The purpose of this study was to develop and validate a deep-learning model for noninvasive anemia detection, hemoglobin (Hb) level estimation, and identification of anemia-related retinal features using fundus images.