Prescriptions

A Machine Learning-Based Model to Predict Acute Traumatic Coagulopathy in Trauma Patients Upon Emergency Hospitalization.

Acute traumatic coagulopathy (ATC) is an extremely common but silent murderer; this condition presents early after trauma and impacts approximately 30% of severely injured patients who are admitted to emergency departments (EDs). Given that conventional coagulation indicators usually require more than 1 hour after admission to yield results-a limitation that frequently prevents the ability for cli...

Realizing the Potential of Robotics for Aged Care Through Co-Creation.

Socially assistive robots have the potential to improve aged care by providing assistance through social interaction. While some evidence suggests a positive impact of social robots on measures of well-being, the adoption of robotic technology remains slow. One approach to improve technology adoption is involving all stakeholders in the process of technology development using co-creation methods. ...

Current Advances and Limitations of Deep Learning in Anticancer Drug Sensitivity Prediction.

Anticancer drug screening can accelerate drug discovery to save the lives of cancer patients, but cancer heterogeneity makes this screening challengin...

Applications of Machine Learning in Drug Target Discovery.

Drug target discovery is a critical step in drug development. It is the basis of modern drug development because it determines the target molecules re...

Medication Adherence and Stroke Prevention: What Real World Data Tells Us.

Medication adherence, by definition,(2) is "the extent to which a patient acts in accordance with the prescribed interval and dose of a dosing regimen...

Reducing drug prescription errors and adverse drug events by application of a probabilistic, machine-learning based clinical decision support system in an inpatient setting.

BACKGROUND: Drug prescription errors are made, worldwide, on a daily basis, resulting in a high burden of morbidity and mortality. Existing rule-based...

Deep neural networks ensemble for detecting medication mentions in tweets.

OBJECTIVE: Twitter posts are now recognized as an important source of patient-generated data, providing unique insights into population health. A fund...

A computational method for design of connected catalytic networks in proteins.

Computational design of new active sites has generally proceeded by geometrically defining interactions between the reaction transition state(s) and s...

Gene-gene interaction: the curse of dimensionality.

Identified genetic variants from genome wide association studies frequently show only modest effects on the disease risk, leading to the "missing heri...

The Mortality and Medical Costs of Air Pollution: Evidence from Changes in Wind Direction.

We estimate the causal effects of acute fine particulate matter exposure on mortality, health care use, and medical costs among the US elderly using M...

Optimization of treatment strategy by using a machine learning model to predict survival time of patients with malignant glioma after radiotherapy.

The purpose of this study was to predict the survival time of patients with malignant glioma after radiotherapy with high accuracy by considering addi...

Ex-vivo antihypertensive and calcium channel blocking activity of Androsace foliosa n-hexane leaves fraction on isolated rabbit aorta.

Hypertension is persistent elevation in blood pressure for 3-4 weeks. Estimated global prevalence of hypertension suggested that by the Year 2025 (29%...

Optimization of diazo dye disappearance by the UV/HO process using the Box-Behnken design.

The purpose of this study was to apply the experimental Box-Behnken design (BBD) to evaluate the effect and, therefore, the optimal values of three ch...

Teaching robots social autonomy from in situ human guidance.

Striking the right balance between robot autonomy and human control is a core challenge in social robotics, in both technical and ethical terms. On th...

Microfluidic cap-to-dispense (μCD): a universal microfluidic-robotic interface for automated pipette-free high-precision liquid handling.

Microfluidic devices have been increasingly used for low-volume liquid handling operations. However, laboratory automation of such delicate devices ha...

Learning to detect and understand drug discontinuation events from clinical narratives.

OBJECTIVE: Identifying drug discontinuation (DDC) events and understanding their reasons are important for medication management and drug safety surve...

Recent applications of deep learning and machine intelligence on in silico drug discovery: methods, tools and databases.

The identification of interactions between drugs/compounds and their targets is crucial for the development of new drugs. In vitro screening experimen...

[Artificial Intelligence-based Drug Discovery and Drug Repositioning].

The methodologies of computational drug discovery and drug repositioning (DR) based on biomolecular profile information are reviewed systematically. F...

Automatic Methods to Extract Prescription Status Quality Measures from Unstructured Health Records.

Hospital systems frequently implement quality measures to quantify healthcare processes and patient outcomes. One such measure that has previously bee...

Improving the Prescription Process Information Support with Structured Medical Prospectuses Using Neural Networks.

To provide the best treatment, a physician needs information about both the patient and the medicines matching the patient status and improving it. In...