Hospital-Based Medicine

Radiomics prediction of surgery in ulcerative colitis refractory to medical treatment.

BACKGROUND: The surgeries in drug-resistant ulcerative colitis are determined by complex factors. This study evaluated the predictive performance of radiomics analysis on the basis of whether patients with ulcerative colitis in hospital were in the surgical or medical treatment group by discharge from hospital.

Deep Learning to Enhance Diagnosis and Management of Intrahepatic Cholangiocarcinoma.

Intrahepatic cholangiocarcinoma (iCCA) is associated with a poor prognosis and necessitates a multimodal, multidisciplinary approach from diagnosis to treatment to achieve optimal outcomes. A noninvasive preoperative diagnosis using abdominal imaging techniques can represent a clinical challenge. Given the differential response of iCCA to localized and systemic therapies compared with hepatocellul...

Are Wearable ECG Devices Ready for Hospital at Home Application?

The increasing focus on improving care for high-cost patients has highlighted the potential of Hospital at Home (HaH) and remote patient monitoring (R...

Starting a synthetic biological intelligence lab from scratch.

Recent advances in artificial intelligence (AI) have led to the development and deployment of gigantic models trained on billions of samples. While tr...

Assessing and validating machine learning-enhanced imputation of admission American Spinal Injury Association Impairment Scale grades for spinal cord injury.

OBJECTIVE: The American Spinal Injury Association Impairment Scale (AIS) assigned at patient admission is an important predictor of outcomes following...

Micro hole drilling and multi criteria optimization of soda lime glass via ultrasonic assisted rotary electrochemical discharge drilling.

Regardless of the materials' intrinsic characteristics, electrochemical discharge drilling (ECDD) effectively micro-machines various materials. The pr...

Machine learning-based prediction of 90-day prognosis and in-hospital mortality in hemorrhagic stroke patients.

This study aims to predict hemorrhagic stroke outcomes, including 90-day prognosis and in-hospital mortality, using machine learning models and SHaple...

Large Language Models in Cancer Imaging: Applications and Future Perspectives.

Recently, there has been tremendous interest on the use of large language models (LLMs) in radiology. LLMs have been employed for various applications...

Development and Validation of Machine Learning Algorithms for Predicting Prolonged Postoperative Opioid Use in Spinal Metastatic Disease.

Introduction: Operative management of spinal metastatic disease is largely for symptom palliation and revolves around the expectation that postoperati...

Prediction of the functional outcome of intensive inpatient rehabilitation after stroke using machine learning methods.

An accurate and reliable functional prognosis is vital to stroke patients addressing rehabilitation, to their families, and healthcare providers. This...

Predicting high-need high-cost pediatric hospitalized patients in China based on machine learning methods.

Rapidly increasing healthcare spending globally is significantly driven by high-need, high-cost (HNHC) patients, who account for the top 5% of annual ...

Predicting onward care needs at admission to reduce discharge delay using explainable machine learning.

Early identification of patients who require onward referral to social care can prevent delays to discharge from hospital. We introduce an explainable...

Early Lung Cancer Patient Journey in Singapore: Challenges and Recommendations.

Early detection of lung cancer is crucial for improving survival rates because it allows for potentially curative treatments; however, most lung cance...

BedreFlyt: Improving Patient Flows through Hospital Wards with Digital Twins

Digital twins are emerging as a valuable tool for short-term decision-making as well as for long-term strategic planning across numerous domains, in...

Insights From Inputs: Enhancing Revision Total Joint Arthroplasty Resource Allocation With Machine Learning Prediction.

BACKGROUND: Revision total knee arthroplasty (rTKA) and revision total hip arthroplasty (rTHA) are among the most resource-intensive orthopaedic proce...

Precision, intelligence, and a new paradigm for chemical research.

Chemists have long struggled to precisely regulate and create substances, often relying on trial-and-error methods that are inefficient for complex, h...

Concordance of ChatGPT artificial intelligence decision-making in colorectal cancer multidisciplinary meetings: retrospective study.

BACKGROUND: The objective of this study was to evaluate the concordance between therapeutic recommendations proposed by a multidisciplinary team meeti...

The Tensor-Core Beamformer: A High-Speed Signal-Processing Library for Multidisciplinary Use

Beamforming is a well-known technique to combine signals from multiple sensors. It has a wide range of application domains. This paper introduces th...

AI-ready Snow Radar Echogram Dataset (SRED) for climate change monitoring

Tracking internal layers in radar echograms with high accuracy is essential for understanding ice sheet dynamics and quantifying the impact of accel...

Early Detection and Remote Care of Frailty for Older Adults Living in Sparsely Populated Rural Areas in Hokkaido, Japan: A Case Study.

The global increase in the number of older people aged 65 and over is causing concern in healthcare and social systems. The lack of health and welfare...