Hospital-Based Medicine

Improving breast cancer care coordination and symptom management by using AI driven predictive toolkits.

Integrated breast cancer care is complex, marked by multiple hand-offs between primary care and specialists over an extensive period of time. Communication is essential for treatment compliance, lowering error and complication risk, as well as handling co-morbidity. The director role of care, however, becomes often unclear, and patients remain lost across departments. Digital tools can add signifi...

The Antifungal Peptide MCh-AMP1 Derived From Inhibits Growth via Inducing ROS Generation and Altering Fungal Cell Membrane Permeability.

The rise of antifungal drug resistance in species responsible for life threatening candidiasis is considered as an increasing challenge for the public health. MCh-AMP1 has previously been reported as a natural peptide from L. flowers with broad-spectrum antifungal activity against human pathogenic molds and yeasts. In the current study, the mode of action of synthetic MCh-AMP1 was investigated a...

Predicting Chronic Subdural Hematoma Recurrence and Stroke Outcomes While Withholding Antiplatelet and Anticoagulant Agents.

The aging of the western population and the increased use of oral anticoagulation (OAC) and antiplatelet drugs (APD) will result in a clinical dilemm...

Dynamic readmission prediction using routine postoperative laboratory results after radical cystectomy.

OBJECTIVE: To determine if the addition of electronic health record data enables better risk stratification and readmission prediction after radical c...

Deep Natural Language Processing Identifies Variation in Care Preference Documentation.

CONTEXT: Documentation of care preferences within 48 hours of admission to an intensive care unit (ICU) is a National Quality Forum-endorsed quality m...

Prediction of general medical admission length of stay with natural language processing and deep learning: a pilot study.

Length of stay (LOS) and discharge destination predictions are key parts of the discharge planning process for general medical hospital inpatients. It...

Comparison of supervised machine learning classification techniques in prediction of locoregional recurrences in early oral tongue cancer.

BACKGROUND: The proper estimate of the risk of recurrences in early-stage oral tongue squamous cell carcinoma (OTSCC) is mandatory for individual trea...

Intracatheter Tissue Plasminogen Activator for Chronic Subdural Hematomas after Failed Bedside Twist Drill Craniostomy: A Retrospective Review.

Introduction Chronic subdural hematomas (cSDH) are common in neurosurgery with various symptoms and significant morbidity and mortality. Treatment var...

Discovery of potential 1,3,5-Triazine compounds against strains of Plasmodium falciparum using supervised machine learning models.

The Malaria burden was an escalating global encumbrance and need to be addressed with critical care. Anti-malarial drug discovery was integrated with ...

Two-in-one method: Novel pancreaticojejunostomy technique for the bifid pancreas.

The bifid pancreas is a rare anatomical variation of the pancreatic duct in which double main pancreatic ducts in the body and tail of the pancreas jo...

Robotic body weight support enables safe stair negotiation in compliance with basic locomotor principles.

BACKGROUND: After a neurological injury, mobility focused rehabilitation programs intensively train walking on treadmills or overground. However, afte...

The impact of extraneous features on the performance of recurrent neural network models in clinical tasks.

Electronic Medical Records (EMR) are a rich source of patient information, including measurements reflecting physiologic signs and administered therap...

Machine learning for the detection of early immunological markers as predictors of multi-organ dysfunction.

The immune response to major trauma has been analysed mainly within post-hospital admission settings where the inflammatory response is already underw...

CAD and AI for breast cancer-recent development and challenges.

Computer-aided diagnosis (CAD) has been a popular area of research and development in the past few decades. In CAD, machine learning methods and multi...

A continual prediction model for inpatient acute kidney injury.

Acute kidney injury (AKI) commonly occurs in hospitalized patients and can lead to serious medical complications. But it is preventable and potentiall...

Implementation of machine learning algorithms to create diabetic patient re-admission profiles.

BACKGROUND: Machine learning is a branch of Artificial Intelligence that is concerned with the design and development of algorithms, and it enables to...

Exploring the perceptions of people with dementia about the social robot PARO in a hospital setting.

New technology, such as social robots, opens up new opportunities in hospital settings. PARO, a robotic pet seal, was designed to provide emotional an...

Spatial Lifecourse Epidemiology Reporting Standards (ISLE-ReSt) statement.

Spatial lifecourse epidemiology is an interdisciplinary field that utilizes advanced spatial, location-based, and artificial intelligence technologies...

Multi-view ensemble learning with empirical kernel for heart failure mortality prediction.

Heart failure (HF) refers to the heart's inability to pump sufficient blood to maintain the body's needs, which has a very serious impact on human hea...

Development and Validation of a Machine Learning Model to Aid Discharge Processes for Inpatient Surgical Care.

IMPORTANCE: Inpatient overcrowding is associated with delays in care, including the deferral of surgical care until beds are available to accommodate ...