AIMC Topic: Algorithms

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Relating molecular descriptors to frontier orbital energy levels, singlet and triplet excited states of fused tricyclics using machine learning.

Journal of molecular graphics & modelling
Fused tricyclic organic compounds are an important class of organic electronic materials. In designing molecules for organic electronics, knowing what chemical structure that be used to tune the molecular property is one of the keys that can help to ...

Evaluation of machine learning algorithms for health and wellness applications: A tutorial.

Computers in biology and medicine
Research on decision support applications in healthcare, such as those related to diagnosis, prediction, treatment planning, etc., has seen strongly growing interest in recent years. This development is thanks to the increase in data availability as ...

Machine learning in Magnetic Resonance Imaging: Image reconstruction.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Magnetic Resonance Imaging (MRI) plays a vital role in diagnosis, management and monitoring of many diseases. However, it is an inherently slow imaging technique. Over the last 20 years, parallel imaging, temporal encoding and compressed sensing have...

Requirements and reliability of AI in the medical context.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
The digital information age has been a catalyst in creating a renewed interest in Artificial Intelligence (AI) approaches, especially the subclass of computer algorithms that are popularly grouped into Machine Learning (ML). These methods have allowe...

Decoding with confidence: Statistical control on decoder maps.

NeuroImage
In brain imaging, decoding is widely used to infer relationships between brain and cognition, or to craft brain-imaging biomarkers of pathologies. Yet, standard decoding procedures do not come with statistical guarantees, and thus do not give confide...

Detecting cerebral microbleeds via deep learning with features enhancement by reusing ground truth.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Cerebral microbleeds (CMBs) are cerebral small vascular diseases and are often used to diagnose symptoms such as stroke and dementia. Manual detection of cerebral microbleeds is a time-consuming and error-prone task, so the...

Locally operated assistant manipulators with selectable connection system for robotically assisted laparoscopic solo surgery.

International journal of computer assisted radiology and surgery
PURPOSE: By integrating locally operated surgical assistant robots in a sterilized area, a surgeon can perform safe robotically assisted laparoscopic solo surgery while controlling a laparoscope-holding robot and a forceps robot. At present, there is...

Incorporating Machine Learning into Established Bioinformatics Frameworks.

International journal of molecular sciences
The exponential growth of biomedical data in recent years has urged the application of numerous machine learning techniques to address emerging problems in biology and clinical research. By enabling the automatic feature extraction, selection, and ge...

NT-FDS-A Noise Tolerant Fall Detection System Using Deep Learning on Wearable Devices.

Sensors (Basel, Switzerland)
Given the high prevalence and detrimental effects of unintentional falls in the elderly, fall detection has become a pertinent public concern. A Fall Detection System (FDS) gathers information from sensors to distinguish falls from routine activities...