Hematology

Real-time and accurate estimation of surgical hemoglobin loss using deep learning-based medical sponges image analysis.

Real-time and accurate estimation of surgical hemoglobin (Hb) loss is essential for fluid resuscitation management and evaluation of surgical techniques. In this study, we aimed to explore a novel surgical Hb loss estimation method using deep learning-based medical sponges image analysis. Whole blood samples of pre-measured Hb concentration were collected, and normal saline was added to simulate v...

Discrimination of human and animal bloodstains using hyperspectral imaging.

Blood is the most encountered type of biological evidence in violent crimes and contains pertinent information to a forensic investigation. The false presumption that blood encountered at a crime scene is human may not be realised until after costly and sample-consuming tests are performed. To address the question of blood origin, the novel application of visible-near infrared hyperspectral imagin...

Robot-assisted versus open radical prostatectomy: a systematic review and meta-analysis of prospective studies.

The study aims to synthesize all available prospective comparative studies and reports the latest systematic analysis and updated evidence comparing r...

Analysis of cortical cell polarity by imaging flow cytometry.

Metastasis is the main cause of cancer-related death and therapies specifically targeting metastasis are highly needed. Cortical cell polarity (CCP) i...

Deep learning-based pigment analysis model trained with optical approach and ground truth assistance.

This study introduces an integrated training method combining the optical approach with ground truth for skin pigment analysis. Deep learning is incre...

Training of epitope-TCR prediction models with healthy donor-derived cancer-specific T cells.

Discovery of epitope-specific T-cell receptors (TCRs) for cancer therapies is a time consuming and expensive procedure that usually requires a large a...

As artificial intelligence goes multimodal, medical applications multiply.

Machines don't have eyes, but you wouldn't know that if you followed the progression of deep learning models for accurate interpretation of medical im...

Rapid Discrimination of ST175 Isolates Involved in a Nosocomial Outbreak Using MALDI-TOF Mass Spectrometry and FTIR Spectroscopy Coupled with Machine Learning.

The goal of this study was to evaluate matrix-assisted laser desorption ionization-iime of flight mass spectrometry (MALDI-TOF MS) and Fourier-transfo...

Data-driven decision-making for precision diagnosis of digestive diseases.

Modern omics technologies can generate massive amounts of biomedical data, providing unprecedented opportunities for individualized precision medicine...

Marker-Free Isoelectric Focusing Patterns for Identification of Meat Samples via Deep Learning.

Isoelectric focusing (IEF) is a powerful tool for resolving complex protein samples, which generates IEF patterns consisting of multiplex analyte band...

Application of artificial neural network in daily prediction of bleeding in ICU patients treated with anti-thrombotic therapy.

OBJECTIVES: Anti-thrombotic therapy is the basis of thrombosis prevention and treatment. Bleeding is the main adverse event of anti-thrombosis. Existi...

Validation of a Parvovirus B19 NAT Assay for Screening of Umbilical Cord Blood for Allogenic Hematopoietic Stem Cell Donation.

INTRODUCTION: Parvovirus B19 transmitted by umbilical cord blood (UCB) products may cause severe disease in allogenic hematopoietic stem cell transpla...

Artificial Intelligence Assists in the Detection of Blood Vessels in Whole Slide Images: Practical Benefits for Oncological Pathology.

The analysis of the microvasculature and the assessment of angiogenesis have significant prognostic value in various diseases, including cancer. The s...

Artificial intelligence and the blood film: Performance of the MC-80 digital morphology analyzer in samples with neoplastic and reactive cell types.

INTRODUCTION: Implementing artificial intelligence-based instruments in hematology laboratories requires evidence of efficiency in classifying patholo...

[Artificial Intelligence for computer-aided leukemia diagnostics].

The manual examination of blood and bone marrow specimens for leukemia patients is time-consuming and limited by intra- and inter-observer variance. T...

Non-invasive hemoglobin estimation from conjunctival images using deep learning.

Hemoglobin, a crucial protein found in erythrocytes, transports oxygen throughout the body. Deviations from optimal hemoglobin levels in the blood are...

iCLOTS: open-source, artificial intelligence-enabled software for analyses of blood cells in microfluidic and microscopy-based assays.

While microscopy-based cellular assays, including microfluidics, have significantly advanced over the last several decades, there has not been concurr...

Perioperative and oncological outcomes of robot-assisted laparoscopic partial nephrectomy for cystic and solid renal masses: Evidence from controlled trials.

To evaluate the outcomes of robot-assisted partial nephrectomy (RAPN) for solid and cystic renal tumors. We systematically searched the Cochrane Libra...

High-accuracy morphological identification of bone marrow cells using deep learning-based Morphogo system.

Accurate identification and classification of bone marrow (BM) nucleated cell morphology are crucial for the diagnosis of hematological diseases. Howe...

A Comparative Analysis of Various Machine Learning Algorithms to Improve the Accuracy of HbA1c Estimation Using Wrist PPG Data.

Due to the inconvenience of drawing blood and the possibility of infection associated with invasive methods, research on non-invasive glycated hemoglo...