AIMC Topic: Humans

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Urine-based Raman markers for prostate cancer diagnosis: A machine learning approach using fingerprint and lipid spectral region.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
This study investigates the potential of Raman spectroscopy in distinguishing between healthy individuals and prostate cancer patients using urine samples. The Boruta algorithm was applied to Raman spectral data in two distinct wavenumber regions: 80...

Diagnostic immune-related markers for diabetic kidney disease: a bioinformatics and machine learning approach.

Renal failure
OBJECTIVE: Diabetic kidney disease (DKD) is a leading cause of chronic kidney disease, with chronic inflammation driving its progression. This study aimed to identify immune-related diagnostic biomarkers for DKD and explore their association with imm...

Epi4Ab: a data-driven prediction model of conformational epitopes for specific antibody VH/VL families and CDRs sequences.

mAbs
Antibodies recognize antigens via complementary and structurally dependent mechanisms. Therefore, inclusion of antibody inputs is crucial for accurate epitope prediction. Given the limited availability of antibody-antigen complex structures, any epit...

A noninvasive and highly efficient epigenetic predictive model for efficacy of the GOLP regimen in patients with intrahepatic cholangiocarcinoma.

Cancer letters
The GOLP regimen (Gemcitabine, Oxaliplatin, Lenvatinib and anti-PD1 antibody) has been a promising first-line treatment for advanced intrahepatic cholangiocarcinoma (iCCA). A noninvasive tool to predict the response to GOLP regimen is needed for clin...

A deep learning-based clinical decision support system for glioma grading using ensemble learning and knowledge distillation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Gliomas are the most common malignant primary brain tumors, and grading their severity, particularly the diagnosis of low-grade gliomas, remains a challenging task for clinicians and radiologists. With advancements in deep learning and medical image ...

Leukocyte analysis: Current status and future direction.

Clinica chimica acta; international journal of clinical chemistry
Leukocytes (white blood cells, WBCs) are a vital component of the human immune system, responsible for resisting foreign pathogens, repairing damaged tissues, and regulating immune responses. Abnormal changes in their number and function serve as cli...

Can AI computing power promote the green transformation of energy enterprises? Evidence from the nonlinear moderating effect of public environmental awareness.

Journal of environmental management
Amid growing concerns over climate change and energy security, the green transformation of energy enterprises has become a global sustainability priority. This study investigates the nonlinear impact of artificial intelligence computing power (AICP) ...

The potential of machine learning to personalized medicine in Neurogenetics: Current trends and future directions.

Computers in biology and medicine
Neurogenetic disorders (NeD) are a group of neurological conditions resulting from inherited genetic defects. By affecting the normal functioning of the nervous system, these diseases lead to serious problems in movement, cognition, and other body fu...

Automated assessment of laparoscopic pattern cutting skills using computer vision and deep learning.

Surgery
BACKGROUND: Pattern cutting assessment in Fundamentals of Laparoscopic Surgery currently relies on manual measurement, which can be time-consuming and prone to variability and human error. An automated, objective assessment system could enhance the e...

Perioperative Quality Initiative consensus statement on goal-directed haemodynamic therapy.

British journal of anaesthesia
Perioperative goal-directed haemodynamic therapy (GDHT) includes a variety of protocolised approaches to the assessment and management of the circulatory system and blood flow for patients undergoing surgery. Here we present updated consensus stateme...