AIMC Topic: Humans

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An integrated machine learning-based model for joint diagnosis of ovarian cancer with multiple test indicators.

Journal of ovarian research
OBJECTIVE: To construct a machine learning diagnostic model integrating feature dimensionality reduction techniques and artificial neural network classifiers to develop the value of clinical routine blood indexes for the auxiliary diagnosis of ovaria...

AI Education for Fourth-Year Medical Students: Two-Year Experience of a Web-Based, Self-Guided Curriculum and Mixed Methods Study.

JMIR medical education
BACKGROUND: Artificial intelligence (AI) and machine learning (ML) are poised to have a substantial impact in the health care space. While a plethora of web-based resources exist to teach programming skills and ML model development, there are few int...

Addressing bias in artificial intelligence for public health surveillance.

Journal of medical ethics
Components of artificial intelligence (AI) for analysing social big data, such as natural language processing (NLP) algorithms, have improved the timeliness and robustness of health data. NLP techniques have been implemented to analyse large volumes ...

Machine Learning and Bias in Medical Imaging: Opportunities and Challenges.

Circulation. Cardiovascular imaging
Bias in health care has been well documented and results in disparate and worsened outcomes for at-risk groups. Medical imaging plays a critical role in facilitating patient diagnoses but involves multiple sources of bias including factors related to...

A multi-branch convolutional neural network for snoring detection based on audio.

Computer methods in biomechanics and biomedical engineering
Obstructive sleep apnea (OSA) is associated with various health complications, and snoring is a prominent characteristic of this disorder. Therefore, the exploration of a concise and effective method for detecting snoring has consistently been a cruc...

Prediction of postoperative gait speed change after bilateral primary total knee arthroplasty in female patients using a machine learning algorithm.

Orthopaedics & traumatology, surgery & research : OTSR
BACKGROUND: An important aim of total knee arthroplasty is to achieve functional recovery, which includes post-operative increase in walking speed. Therefore, predicting whether a patient will walk faster or slower after surgery is important in TKA, ...

Twelve tips for Natural Language Processing in medical education program evaluation.

Medical teacher
With the increasing application of Natural Language Processing (NLP) in Medicine at large, medical educators are urged to gain an understanding and implement NLP techniques within their own education programs to improve the workflow and make signific...

Ranking and filtering of neuropathology features in the machine learning evaluation of dementia studies.

Brain pathology (Zurich, Switzerland)
Early diagnosis of dementia diseases, such as Alzheimer's disease, is difficult because of the time and resources needed to perform neuropsychological and pathological assessments. Given the increasing use of machine learning methods to evaluate neur...

Conversational artificial intelligence: the interface with the patient concerns inventory.

The British journal of oral & maxillofacial surgery
The patient concerns inventory (PCI) allows patients to highlight the issues they would like to discuss at their outpatient consultation. It improves patient-clinician communication and has proven benefits. While the PCI is effective, patient experie...

A machine-learning exploration of the exposome from preconception in early childhood atopic eczema, rhinitis and wheeze development.

Environmental research
BACKGROUND: Most previous research on the environmental epidemiology of childhood atopic eczema, rhinitis and wheeze is limited in the scope of risk factors studied. Our study adopted a machine learning approach to explore the role of the exposome st...