Anemia

Metabolomics as a tool for understanding and treating triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is an aggressive and heterogeneous variant of breast cancer distinguished by a lack of targeted therapies, posing significant challenges in diagnosis and treatment. Metabolomics, the comprehensive study of small compounds in biological systems, has been identified as an instrument for revealing the metabolic underpinnings of TNBC. This review highlights recent ...

Promoting active health with AI technologies: Current status and prospects of high-altitude therapy, simulated hypoxia, and LLM-driven lifestyle rehabilitation approaches.

In the context of the rising global prevalence of obesity, traditional intervention measures have proven insufficient to meet the demands of personalized and sustainable health management, necessitating the exploration of innovative solutions through innovative technologies. This study explores how advanced digital technologies, including Internet of Things (IoT) and Artificial Intelligence (AI), ...

Detection of β-Thalassemia trait from a heterogeneous population with red cell indices and parameters.

BACKGROUND: India is home to about 42 million people with β-thalassemia trait (βTT) necessitating screening of βTT to stop spread of the disease. Over...

Exploring hypoxia driven subtypes of pulmonary arterial hypertension through transcriptomics single cell sequencing and machine learning.

Pulmonary arterial hypertension (PAH) is a progressive cardiovascular disease characterized by elevated pulmonary arterial pressure, leading to right ...

Optimizing machine learning models for predicting anemia among under-five children in Ethiopia: insights from Ethiopian demographic and health survey data.

BACKGROUND: Healthcare practitioners require a robust predictive system to accurately diagnose diseases, especially in young children with conditions ...

A comprehensive case study of deep learning on the detection of alpha thalassemia and beta thalassemia using public and private datasets.

This study explores the performance of deep learning models, specifically Convolutional Neural Networks (CNN) and XGBoost, in predicting alpha and bet...

Development of a Deep-Learning-Based Computerized Scoring Algorithm.

During polygraph tests, the examiner evaluates physiological responses recorded on a chart to identify deception. Generally, this evaluation involves ...

Sonopermeation combined with stroma normalization enables complete cure using nano-immunotherapy in murine breast tumors.

Nano-immunotherapy shows great promise in improving patient outcomes, as seen in advanced triple-negative breast cancer, but it does not cure the dise...

Estimating gait parameters from sEMG signals using machine learning techniques under different power capacity of muscle.

The gait analysis has been applied in many fields, such as the assessment of falling, force evaluation in sports, and gait disorder detection for neur...

Machine Learning Models of Early Longitudinal Toxicity Trajectories Predict Cetuximab Concentration and Metastatic Colorectal Cancer Survival in the Canadian Cancer Trials Group/AGITG CO.17/20 Trials.

PURPOSE: Cetuximab (CET), targeting the epidermal growth factor receptor, is a systemic treatment option for patients with colorectal cancer. One know...

Optimized driver fatigue detection method using multimodal neural networks.

Driver fatigue is a significant factor contributing to road accidents, highlighting the need for precise and reliable detection systems. This study in...

DP-MP: a novel cross-subject fatigue detection framework with DANN-based prototypical representation and mix-up pairwise learning.

. Electroencephalography (EEG) is widely recognized as an effective method for detecting fatigue. However, practical applications of EEG for fatigue d...

Direct-acting antivirals (DAA) positively affect depression and cognitive function in patients with chronic hepatitis C.

The aim of the study was to determine how depression and cognitive dysfunction in patients with chronic hepatitis C virus (HCV) infection are affected...

Revolutionizing hematological disorder diagnosis: unraveling the role of artificial intelligence.

The integration of artificial intelligence (AI) into medical diagnostics is transforming the landscape of healthcare, particularly in hematology. AI t...

Shengxuebao Mixture improves carboplatin-induced anemia by inhibiting apoptosis and ferroptosis.

ETHNOPHARMACOLOGICAL RELEVANCE: Shengxuebao Mixture (SXB) is a traditional Chinese medicine which has been widely used on treating Chemotherapy-induce...

Water quality parameters-based prediction of dissolved oxygen in estuaries using advanced explainable ensemble machine learning.

The dissolved oxygen (DO) is crucial for the ecological health of estuaries and bays. However, human activities, land-sea interactions, and the unclea...

Acute mountain sickness prediction: a concerto of multidimensional phenotypic data and machine learning strategies in the framework of predictive, preventive, and personalized medicine.

BACKGROUND: Acute mountain sickness (AMS) is a self-limiting illness, involving a complex series of physiological responses to rapid ascent to high al...

Influence pathways of noise exposure on people's negative emotions and health across different activity contexts: A neural network-based double machine learning approach.

Noise is a major global environmental issue that raises concerns about both mental and physical health. However, few studies have investigated the med...

Gold nanorods as multidimensional optical nanomaterials: machine learning-enhanced quantitative fingerprinting of proteins for diagnostic applications.

The rapid and precise quantification and identification of proteins as key diagnostic biomarkers hold significant promise in allergy testing, disease ...

Machine learning based intratumor heterogeneity related signature for prognosis and drug sensitivity in breast cancer.

Intratumor heterogeneity (ITH) is involved in tumor evolution and drug resistance. Drug sensitivity shows discrepancy in different breast cancer (BRCA...