AIMC Topic: Humans

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AI-Generated Draft Replies Integrated Into Health Records and Physicians' Electronic Communication.

JAMA network open
IMPORTANCE: Timely tests are warranted to assess the association between generative artificial intelligence (GenAI) use and physicians' work efforts.

Convolutional neural network deep learning model accurately detects rectal cancer in endoanal ultrasounds.

Techniques in coloproctology
BACKGROUND: Imaging is vital for assessing rectal cancer, with endoanal ultrasound (EAUS) being highly accurate in large tertiary medical centers. However, EAUS accuracy drops outside such settings, possibly due to varied examiner experience and fewe...

User Experience Evaluation of a Spinal Surgery Robot: Workload, Usability, and Satisfaction Study.

JMIR human factors
BACKGROUND: Robotic spine surgery has continued to evolve since its US Food and Drug Administration approval in 2004, with products now including real-time video guidance and navigation during surgery. As the market for robotic surgical devices evolv...

Feasibility of Robot-Assisted Cytoreductive Surgery With Upper-Abdominal Peritonectomy for Pseudomyxoma Peritonei With Low Peritoneal Carcinomatosis Index: A Pilot Study.

Surgical laparoscopy, endoscopy & percutaneous techniques
INTRODUCTION: Our study's objective was to provide the method for, and preliminary findings from, robot-assisted cytoreductive surgery (r-CRS) combined with upper-abdominal peritonectomy in pseudomyxoma peritonei (PMP) with limited peritoneal surface...

Predicting operative time for metabolic and bariatric surgery using machine learning models: a retrospective observational study.

International journal of surgery (London, England)
BACKGROUND: Predicting operative time is essential for scheduling surgery and managing the operating room. This study aimed to develop machine learning (ML) models to predict the operative time for metabolic and bariatric surgery (MBS) and to compare...

Deep Learning in High-Resolution Anoscopy: Assessing the Impact of Staining and Therapeutic Manipulation on Automated Detection of Anal Cancer Precursors.

Clinical and translational gastroenterology
INTRODUCTION: High-resolution anoscopy (HRA) is the gold standard for detecting anal squamous cell carcinoma (ASCC) precursors. Preliminary studies on the application of artificial intelligence (AI) models to this modality have revealed promising res...

Machine learning prediction model of major adverse outcomes after pediatric congenital heart surgery: a retrospective cohort study.

International journal of surgery (London, England)
BACKGROUND: Major adverse postoperative outcomes (APOs) can greatly affect mortality, hospital stay, care management and planning, and quality of life. This study aimed to evaluate the performance of five machine learning (ML) algorithms for predicti...

Real-time classification of tumour and non-tumour tissue in colorectal cancer using diffuse reflectance spectroscopy and neural networks to aid margin assessment.

International journal of surgery (London, England)
BACKGROUND: Colorectal cancer is the third most commonly diagnosed malignancy and the second leading cause of mortality worldwide. A positive resection margin following surgery for colorectal cancer is linked with higher rates of local recurrence and...

A radiogenomic multimodal and whole-transcriptome sequencing for preoperative prediction of axillary lymph node metastasis and drug therapeutic response in breast cancer: a retrospective, machine learning and international multicohort study.

International journal of surgery (London, England)
BACKGROUND: Axillary lymph nodes (ALN) status serves as a crucial prognostic indicator in breast cancer (BC). The aim of this study was to construct a radiogenomic multimodal model, based on machine learning and whole-transcriptome sequencing (WTS), ...

Population-Specific Glucose Prediction in Diabetes Care With Transformer-Based Deep Learning on the Edge.

IEEE transactions on biomedical circuits and systems
Leveraging continuous glucose monitoring (CGM) systems, real-time blood glucose (BG) forecasting is essential for proactive interventions, playing a crucial role in enhancing the management of type 1 diabetes (T1D) and type 2 diabetes (T2D). However,...