Anemia

Natural language processing of electronic health records is superior to billing codes to identify symptom burden in hemodialysis patients.

Symptoms are common in patients on maintenance hemodialysis but identification is challenging. New informatics approaches including natural language processing (NLP) can be utilized to identify symptoms from narrative clinical documentation. Here we utilized NLP to identify seven patient symptoms from notes of maintenance hemodialysis patients of the BioMe Biobank and validated our findings using ...

ThalPred: a web-based prediction tool for discriminating thalassemia trait and iron deficiency anemia.

BACKGROUND: The hypochromic microcytic anemia (HMA) commonly found in Thailand are iron deficiency anemia (IDA) and thalassemia trait (TT). Accurate discrimination between IDA and TT is an important issue and better methods are urgently needed. Although considerable RBC formulas and indices with various optimal cut-off values have been developed, distinguishing between IDA and TT is still a challe...

A novel automated image analysis system using deep convolutional neural networks can assist to differentiate MDS and AA.

Detection of dysmorphic cells in peripheral blood (PB) smears is essential in diagnostic screening of hematological diseases. Myelodysplastic syndrome...

A LightGBM-Based EEG Analysis Method for Driver Mental States Classification.

Fatigue driving can easily lead to road traffic accidents and bring great harm to individuals and families. Recently, electroencephalography- (EEG-) b...

The future of endoscopy: Advances in endoscopic image innovations.

The latest state of the art technological innovations have led to a palpable progression in endoscopic imaging and may facilitate standardisation of p...

Anemia and iron deficiency among chronic kidney disease Stages 3-5ND patients in the Chronic Kidney Disease Outcomes and Practice Patterns Study: often unmeasured, variably treated.

BACKGROUND: International variation in anemia assessment and management practices in chronic kidney disease (CKD) is poorly understood.

Semi-Supervised Learning Algorithm for Identifying High-Priority Drug-Drug Interactions Through Adverse Event Reports.

Identifying drug-drug interactions (DDIs) is a critical enabler for reducing adverse drug events and improving patient safety. Generating proper DDI a...

Artificial neural networks reveal individual differences in metacognitive monitoring of memory.

Previous work supports an age-specific impairment for recognition memory of pairs of words and other stimuli. The present study tested the generalizat...

Evaluation and Identification of the Neuroprotective Compounds of Xiaoxuming Decoction by Machine Learning: A Novel Mode to Explore the Combination Rules in Traditional Chinese Medicine Prescription.

Xiaoxuming decoction (XXMD), a classic traditional Chinese medicine (TCM) prescription, has been used as a therapeutic in the treatment of stroke in c...

Exploring the druggable space around the Fanconi anemia pathway using machine learning and mechanistic models.

BACKGROUND: In spite of the abundance of genomic data, predictive models that describe phenotypes as a function of gene expression or mutations are di...

Effect of EMG-biofeedback robotic-assisted body weight supported treadmill training on walking ability and cardiopulmonary function on people with subacute spinal cord injuries - a randomized controlled trial.

BACKGROUND: Body weight supported treadmill training (BWSTT) is a frequently used approach for restoring the ability to walk after spinal cord injury ...

Effects of early high-dose erythropoietin on acute kidney injury following cardiac arrest: exploratory analyses from an open-label randomized trial.

BACKGROUND: Acute kidney injury (AKI) is frequent in patients resuscitated from cardiac arrest (CA) and may worsen outcome. Experimental data suggest ...

A Machine Learning Approach to Classifying Self-Reported Health Status in a Cohort of Patients With Heart Disease Using Activity Tracker Data.

Constructing statistical models using personal sensor data could allow for tracking health status over time, thereby enabling the possibility of early...

Ascending Lipopolysaccharide-Induced Intrauterine Inflammation in Near-Term Rabbits Leading to Newborn Neurobehavioral Deficits.

BACKGROUND: Chorioamnionitis from ascending bacterial infection through the endocervix is a potential risk factor for cerebral palsy. Tetrahydrobiopte...

Potential of Parameters of Iron Metabolism for the Diagnosis of Anemia of Inflammation in the Critically Ill.

BACKGROUND: Anemia of inflammation (AI) is the most common cause of anemia in the critically ill, but its diagnosis is a challenge. New therapies spec...

Duplicate portion sampling gives the most accurate iron intake estimate: Implications for iron status of female students.

Iron deficiency (ID) is one of the most common nutritional problems in the developing world, affecting primarily women of childbearing age. Poor dieta...

Differences in muscle activity and fatigue of the upper limb between Task-Specific training and robot assisted training among individuals post stroke.

OBJECTIVE: To compare the activity and fatigue of upper extremity muscles, pain levels, subject satisfaction levels, perceived exertion, and number of...

DDOT: A Swiss Army Knife for Investigating Data-Driven Biological Ontologies.

Systems biology requires not only genome-scale data but also methods to integrate these data into interpretable models. Previously, we developed appro...

Artificial intelligence based discovery of the association between depression and chronic fatigue syndrome.

BACKGROUND: Both of the modern medicine and the traditional Chinese medicine classify depressive disorder (DD) and chronic fatigue syndrome (CFS) to o...

Hybrid Rehabilitation Therapies on Upper-Limb Function and Goal Attainment in Chronic Stroke.

This study examined the treatment effects between unilateral hybrid therapy (UHT; unilateral robot-assisted therapy [RT] + modified constraint-induced...