AIMC Topic: Humans

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Intraoperative near infrared functional imaging of rectal cancer using artificial intelligence methods - now and near future state of the art.

European journal of nuclear medicine and molecular imaging
Colorectal cancer remains a major cause of cancer death and morbidity worldwide. Surgery is a major treatment modality for primary and, increasingly, secondary curative therapy. However, with more patients being diagnosed with early stage and premali...

Consistency of the Signature of Phonotraumatic Vocal Hyperfunction Across Different Ambulatory Voice Measures.

Journal of speech, language, and hearing research : JSLHR
PURPOSE: Although different factors and voice measures have been associated with phonotraumatic vocal hyperfunction (PVH), it is unclear what percentage of individuals with PVH exhibit such differences during their daily lives. This study used a mach...

Artificial intelligence and radiologists in prostate cancer detection on MRI (PI-CAI): an international, paired, non-inferiority, confirmatory study.

The Lancet. Oncology
BACKGROUND: Artificial intelligence (AI) systems can potentially aid the diagnostic pathway of prostate cancer by alleviating the increasing workload, preventing overdiagnosis, and reducing the dependence on experienced radiologists. We aimed to inve...

SEP-AlgPro: An efficient allergen prediction tool utilizing traditional machine learning and deep learning techniques with protein language model features.

International journal of biological macromolecules
Allergy is a hypersensitive condition in which individuals develop objective symptoms when exposed to harmless substances at a dose that would cause no harm to a "normal" person. Most current computational methods for allergen identification rely on ...

Exome sequence analysis identifies rare coding variants associated with a machine learning-based marker for coronary artery disease.

Nature genetics
Coronary artery disease (CAD) exists on a spectrum of disease represented by a combination of risk factors and pathogenic processes. An in silico score for CAD built using machine learning and clinical data in electronic health records captures disea...

Deep learning model utilizing clinical data alone outperforms image-based model for hernia recurrence following abdominal wall reconstruction with long-term follow up.

Surgical endoscopy
BACKGROUND: Deep learning models (DLMs) using preoperative computed tomography (CT) imaging have shown promise in predicting outcomes following abdominal wall reconstruction (AWR), including component separation, wound complications, and pulmonary fa...

Quantifying social capital creation in post-disaster recovery aid in Indonesia: methodological innovation by an AI-based language model.

Disasters
Smooth interaction with a disaster-affected community can create and strengthen its social capital, leading to greater effectiveness in the provision of successful post-disaster recovery aid. To understand the relationship between the types of intera...

Artificial Intelligence Improves the Ability of Physicians to Identify Prostate Cancer Extent.

The Journal of urology
PURPOSE: Defining prostate cancer contours is a complex task, undermining the efficacy of interventions such as focal therapy. A multireader multicase study compared physicians' performance using artificial intelligence (AI) vs standard-of-care metho...

Unraveling the multiple chronic conditions patterns among people with Alzheimer's disease and related dementia: A machine learning approach to incorporate synergistic interactions.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Most people with Alzheimer's disease and related dementia (ADRD) also suffer from two or more chronic conditions, known as multiple chronic conditions (MCC). While many studies have investigated the MCC patterns, few studies have consid...