AIMC Topic: Machine Learning

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Accelerating antibiotic discovery through artificial intelligence.

Communications biology
By targeting invasive organisms, antibiotics insert themselves into the ancient struggle of the host-pathogen evolutionary arms race. As pathogens evolve tactics for evading antibiotics, therapies decline in efficacy and must be replaced, distinguish...

Automated machine learning for endemic active tuberculosis prediction from multiplex serological data.

Scientific reports
Serological diagnosis of active tuberculosis (TB) is enhanced by detection of multiple antibodies due to variable immune responses among patients. Clinical interpretation of these complex datasets requires development of suitable algorithms, a time c...

Machine Learning augmented docking studies of aminothioureas at the SARS-CoV-2-ACE2 interface.

PloS one
The current pandemic outbreak clearly indicated the urgent need for tools allowing fast predictions of bioactivity of a large number of compounds, either available or at least synthesizable. In the computational chemistry toolbox, several such tools ...

Glomerular disease classification and lesion identification by machine learning.

Biomedical journal
BACKGROUND: Classification of glomerular diseases and identification of glomerular lesions require careful morphological examination by experienced nephropathologists, which is labor-intensive, time-consuming, and prone to interobserver variability. ...

Machine learning based early mortality prediction in the emergency department.

International journal of medical informatics
BACKGROUND: It is a great challenge for emergency physicians to early detect the patient's deterioration and prevent unexpected death through a large amount of clinical data, which requires sufficient experience and keen insight.

Machine-learning-based COVID-19 mortality prediction model and identification of patients at low and high risk of dying.

Critical care (London, England)
BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic caused by the SARS-Cov2 virus has become the greatest health and controversial issue for worldwide nations. It is associated with different clinical manifestations and a high mortality rate...

Multivariate random forest prediction of poverty and malnutrition prevalence.

PloS one
Advances in remote sensing and machine learning enable increasingly accurate, inexpensive, and timely estimation of poverty and malnutrition indicators to guide development and humanitarian agencies' programming. However, state of the art models ofte...

Utility of machine learning algorithms in degenerative cervical and lumbar spine disease: a systematic review.

Neurosurgical review
Machine learning is a rapidly evolving field that offers physicians an innovative and comprehensive mechanism to examine various aspects of patient data. Cervical and lumbar degenerative spine disorders are commonly age-related disease processes that...

Detection of sarcopenic obesity and prediction of long-term survival in patients with gastric cancer using preoperative computed tomography and machine learning.

Journal of surgical oncology
BACKGROUND: Previous studies evaluating the prognostic value of computed tomography (CT)-derived body composition data have included few patients. Thus, we assessed the prevalence and prognostic value of sarcopenic obesity in a large population of ga...