AIMC Topic: Humans

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A semi-supervised convolutional neural network for diagnosis of pancreatic ductal adenocarcinoma based on EUS-FNA cytological images.

BMC cancer
BACKGROUND: The cytological diagnostic process of EUS-FNA smears is time-consuming and manpower-intensive, and the conclusion could be subjective and controversial. Moreover, the relative lack of cytopathologists has limited the widespread implementa...

Utilizing machine learning algorithms for predicting Anxiety-Depression Comorbidity Syndrome in Gastroenterology Inpatients (ADCS-GI).

BMC psychiatry
BACKGROUND: Accurately diagnosing Anxiety-Depression Comorbidity Syndrome in Gastroenterology Inpatients (ADCS-GI) shows significant challenges as traditional diagnostic methods fail to meet expectations due to patient hesitance and non-psychiatric h...

Real-world insights of patient voices with age-related macular degeneration in the Republic of Korea and Taiwan: an AI-based Digital Listening study by Semantic-Natural Language Processing.

BMC medical informatics and decision making
BACKGROUND: In this era of active online communication, patients increasingly share their healthcare experiences, concerns, and needs across digital platforms. Leveraging these vast repositories of real-world information, Digital Listening enables th...

Deep learning based on intratumoral heterogeneity predicts histopathologic grade of hepatocellular carcinoma.

BMC cancer
OBJECTIVES: The potential of medical imaging to non-invasively assess intratumoral heterogeneity (ITH) is increasingly being recognized. This study aimed to investigate the value of the ITH-based deep learning model for preoperative prediction of his...

Leveraging machine learning for precision medicine: a predictive model for cognitive impairment in cholestasis patients.

BMC gastroenterology
BACKGROUND: Cholestasis, characterized by impaired bile flow, impacts cognitive function through systemic mechanisms, including inflammation and metabolic dysregulation. Despite its significance, targeted predictive models for cognitive impairment in...

Using artificial intelligence for systematic review: the example of elicit.

BMC medical research methodology
BACKGROUND: Artificial intelligence (AI) tools are increasingly being used to assist researchers with various research tasks, particularly in the systematic review process. Elicit is one such tool that can generate a summary of the question asked, se...

International expert consensus on the current status and future prospects of artificial intelligence in metabolic and bariatric surgery.

Scientific reports
Artificial intelligence (AI) is transforming the landscape of medicine, including surgical science and practice. The evolution of AI from rule-based systems to advanced machine learning and deep learning algorithms has opened new avenues for its appl...

A novel deep sequential learning architecture for drug drug interaction prediction using DDINet.

Scientific reports
Drug drug Interactions (DDI) present considerable challenges in healthcare, often resulting in adverse effects or decreased therapeutic efficacy. This article proposes a novel deep sequential learning architecture called DDINet to predict and classif...

Innovative hand pose based sign language recognition using hybrid metaheuristic optimization algorithms with deep learning model for hearing impaired persons.

Scientific reports
Sign language (SL) is an effective mode of communication, which uses visual-physical methods like hand signals, expressions, and body actions to communicate between the difficulty of hearing and the deaf community, produce opinions, and carry signifi...

Life's Crucial 9 and NAFLD from association to SHAP-interpreted machine learning predictions.

Scientific reports
Non-alcoholic fatty liver disease (NAFLD) is the most prevalent chronic liver disease worldwide. Cardiovascular disease (CVD) and NAFLD share multiple common risk factors. Life's Crucial 9 (LC9), a novel indicator for comprehensive assessment of card...