Prevention of medical errors

Accuracy and Reliability of ChatGPT in Answering Patient Questions About Lung Cancer and Its Surgery: An Expert Panel Evaluation by Thoracic Surgeons.

This study aimed to evaluate the accuracy, clarity, and scientific adequacy of ChatGPT's responses to frequently asked patient questions concerning lung cancer and its surgical treatment, through an expert panel of thoracic surgeons. A total of 36 frequently asked questions-20 related to lung cancer and 16 related to lung cancer surgery-were collected from various online sources and clinical exper...

A model based on artificial intelligence for the prediction, prevention and patient-centred approach for non-communicable diseases related to metabolic syndrome.

Metabolic syndrome (MetS) is related to non-communicable diseases (NCDs) such as type 2 diabetes (T2D), metabolic-associated steatotic liver disease (MASLD), atherogenic dyslipidaemia (ATD), and chronic kidney disease (CKD). The absence of reliable tools for early diagnosis and risk stratification leads to delayed detection, preventable hospitalizations, and increased healthcare costs. This study ...

Exploring the impact of neutrophils on lung adenocarcinoma using Mendelian randomization and transcriptomic study.

Tumor immune microenvironment plays a crucial role in determining the prognosis of lung adenocarcinoma (LUAD), with the interaction of immune cells wi...

An Interpretable Artificial Intelligence System for Crohn's Disease Ulcer Identification and Grading on Double-Balloon Enteroscopy Images.

BACKGROUND: Crohn's disease (CD) is an incurable inflammatory bowel disease that can lead to a variety of complications and requires lifelong treatmen...

Polar code construction by estimating noise using bald hawk optimized recurrent neural network model.

Polar codes are making significant progress in error-correcting coding due to their ability to reach the limit of the Shannon capacity of communicatio...

Intelligent diagnosis model for chest X-ray images diseases based on convolutional neural network.

To address misdiagnosis caused by feature coupling in multi-label medical image classification, this study introduces a chest X-ray pathology reasonin...

Iron metabolism and preeclampsia: new insights from bioinformatics analysis.

OBJECTIVE: Preeclampsia (PE) is a multifactorial systemic pregnancy disease, in which iron metabolism and ferroptosis play significant roles during it...

Enhancing anomaly detection and prevention in Internet of Things (IoT) using deep neural networks and blockchain based cyber security.

The rapid adoption of Internet of Things (IoT) devices has significantly increased cybersecurity risks, making them vulnerable to anomalies, attacks, ...

Deep learning based predictive models for real time accident prevention in autonomous vehicle networks.

There have been substantial difficulties to road safety brought about by the increasing volume of traffic, which has resulted in the requirement for s...

Improving EEG based brain computer interface emotion detection with EKO ALSTM model.

Decoding signals from the CNS brain activity is done by a computer-based communication device called a BCI. In contrast, the system is considered comp...

A fiber channel modeling method based on complex neural networks.

Channel modeling plays a pivotal role in the field of communications, particularly in the optical communication networks of backbone communication sys...

PM concentration 7-day prediction in the Beijing-Tianjin-Hebei region using a novel stacking framework.

High-precision prediction of near-surface PM concentration is a significant theoretical prerequisite for effective monitoring and prevention of air po...

Machine learning and transformer models for prediction of postoperative pneumonia risk in patients with lower limb fractures.

Postoperative pneumonia, a prevalent complication arising from lower limb fracture surgery, can significantly prolong hospitalization periods and elev...

[Artificial intelligence in preventive medicine for children and adolescents-applications and acceptance].

The use of artificial intelligence (AI) in pediatric and adolescent medicine offers numerous possibilities, particularly in the prevention of chronic ...

Proposal for Using AI to Assess Clinical Data Integrity and Generate Metadata: Algorithm Development and Validation.

BACKGROUND: Evidence-based medicine combines scientific research, clinical expertise, and patient preferences to enhance the patient outcomes and impr...

An Artificial Intelligence Tool for the Diagnosis of Facial Pain.

BACKGROUND AND OBJECTIVES: Differentiation between temporomandibular disorders (TMDs) and trigeminal neuralgia (TN) as causes of orofacial pain is ver...

Artificial Intelligence-Based Detection of Central Retinal Artery Occlusion Within 4.5 Hours on Standard Fundus Photographs.

BACKGROUND: Prompt diagnosis of acute central retinal artery occlusion (CRAO) is crucial for therapeutic management and stroke prevention. However, mo...

A Wearable AI-Driven Mask with Humidity-Sensing Respiratory Microphone for Non-Vocal Communication.

Hoarseness and dysphonia caused by vocal cord conditions or laryngeal surgeries significantly hinder communication and quality of life. This study pre...

Identification of individuals who benefit from omega-3 fatty acid supplementation to prevent coronary heart disease: a machine-learning analysis of the VITAL.

Randomized controlled trials (RCTs) have demonstrated benefits of marine omega-3 polyunsaturated fatty acids (omega-3 FA) supplementation for the prev...

Deep learning classification of drug-related problems from pharmaceutical interventions issued by hospital clinical pharmacists during medication prescription review: a large-scale descriptive retrospective study in a French university hospital.

OBJECTIVES: Pharmaceutical interventions are proposals made by hospital clinical pharmacists to address sub-optimal uses of medications during prescri...