AIMC Topic: Adult

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Development of Machine Learning Models for Predicting Postoperative Delayed Remission in Patients With Cushing's Disease.

The Journal of clinical endocrinology and metabolism
CONTEXT: Postoperative hypercortisolemia mandates further therapy in patients with Cushing's disease (CD). Delayed remission (DR) is defined as not achieving postoperative immediate remission (IR), but having spontaneous remission during long-term fo...

Technology Can Augment, but Not Replace, Critical Human Skills Needed for Patient Care.

Academic medicine : journal of the Association of American Medical Colleges
The practice of medicine is changing rapidly as a consequence of electronic health record adoption, new technologies for patient care, disruptive innovations that breakdown professional hierarchies, and evolving societal norms. Collectively, these ha...

Differentiation of rare brain tumors through unsupervised machine learning: Clinical significance of in-depth methylation and copy number profiling illustrated through an unusual case of IDH wildtype glioblastoma.

Clinical neuropathology
Methylation profiling has become a mainstay in brain tumor diagnostics since the introduction of the first publicly available classification tool by the German Cancer Research Center in 2017. We demonstrate the capability of this system through an ex...

Constipation Predominant Irritable Bowel Syndrome and Functional Constipation Are Not Discrete Disorders: A Machine Learning Approach.

The American journal of gastroenterology
INTRODUCTION: Chronic constipation is classified into 2 main syndromes, irritable bowel syndrome with constipation (IBS-C) and functional constipation (FC), on the assumption that they differ along multiple clinical characteristics and are plausibly ...

Artificial Intelligence and Clinical Decision Making: The New Nature of Medical Uncertainty.

Academic medicine : journal of the Association of American Medical Colleges
Estimates in a 1989 study indicated that physicians in the United States were unable to reach a diagnosis that accounted for their patient's symptoms in up to 90% of outpatient patient encounters. Many proponents of artificial intelligence (AI) see t...

Determination of disease severity in COVID-19 patients using deep learning in chest X-ray images.

Diagnostic and interventional radiology (Ankara, Turkey)
PURPOSE: Chest X-ray plays a key role in diagnosis and management of COVID-19 patients and imaging features associated with clinical elements may assist with the development or validation of automated image analysis tools. We aimed to identify associ...

A Deep Neural Network to Distinguish COVID-19 from other Chest Diseases Using X-ray Images.

Current medical imaging
BACKGROUND: Scanning a patient's lungs to detect Coronavirus 2019 (COVID-19) may lead to similar imaging of other chest diseases. Thus, a multidisciplinary approach is strongly required to confirm the diagnosis. There are only a few works targeted at...

[Risk factors for multiple debridements of the patients with deep incisional surgical site infection after spinal surgery].

Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences
OBJECTIVE: To investigate the risk factors that contribute to multiple debridements in patients suffering from deep incisional surgical site infection after spinal surgery and advise medical personnel to pay special attention to these risk factors.

Dermoscopic Features of Giant Molluscum Contagiosum in a Patient with Acquired Immunodeficiency Syndrome.

Acta dermatovenerologica Croatica : ADC
Giant molluscum contagiosum (MC) is a peculiar variant of the disease with the presence of multiple or single lesions larger than 5 mm. In contrast to typical molluscum contagiosum, dermoscopic features of giant lesions have been poorly described, an...