Unravelling healthcare complexity – a machine learning perspective.

Unravelling healthcare complexity – a machine learning perspective.

The arc of history drawn by Sir Cyril Chantler in 1999 is increasingly clear; “Medicine used to be simple, ineffective, and relatively safe. Now it is complex, effective, and potentially dangerous”. Rising complexity in healthcare, results in ineffective decision-making that leads to detrimental effects on care quality and escalates costs. This viewpoint motivates with examples the usefulness of predictive Machine Learning (ML) models to unravel healthcare complexity which has a clinical and an administrative perspective; and emphasizes to unleashElectronic Health Record (EHR) functionality – while duly respecting all ethical and legal concerns – to reap full benefits of ML. From an administrative perspective, an important source of complexity is...

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Learning clinical vectors from structured Electronic health records

Learning efficient and dense real-valued representations of high dimensional clinical codes remain a key challenge in data-driven clinical applications like predictive modelling, comparative effectiveness research and more. In this study, we used a slightly modified version of word2vec (a word embedding technique) to vectorise diagnostic and medication codes in structured electronic health record (EHR) – MIMIC-III. Given a list of clinical codes corresponding to a hospital visit, a shallow one-hidden layer neural network was trained to predict all neighbouring codes in the visit from a single code. Once trained, the input-hidden layer weights were used as the embedding matrix to represent each clinical code. In comparison to the traditional one-hot format,...

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A modified fuzzy C means algorithm for shading correction in craniofacial CBCT images

CBCT images suffer from acute shading artifacts primarily due to scatter. Numerous image-domain correction algorithms have been proposed in the literature that uses patient-specific planning CT images to estimate shading contributions in CBCT images. However, in the context of radiosurgery applications such as gamma knife, planning images are often acquired through MRI which impedes the use of polynomial fitting approaches for shading correction. We present a new shading correction approach that is independent of planning CT images. Our algorithm is based on the assumption that true CBCT images follow a uniform volumetric intensity distribution per material, and scatter perturbs this uniform texture by contributing cupping and shading artifacts in the image...

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Segmentation of Cone Beam CT in Stereotactic Radiosurgery

C-arm Cone Beam CT (CBCT) systems – due to compact size, flexible geometry and low radiation exposure – inaugurated the era of on-board 3D image guidance in therapeutic and surgical procedures. Leksell Gamma Knife Icon by Elekta introduced an integrated CBCT system to determine patient position prior to surgical session, thus advancing to a paradigm shift in facilitating frameless stereotactic radiosurgeries. While CBCT offers a quick imaging facility with high spatial accuracy, the quantitative values tend to be distorted due to various physics based artifacts such as scatter, beam hardening and cone beam effect. Several 3D reconstruction algorithms targeting these artifacts involve an accurate and fast segmentation of craniofacial CBCT images into air, tissue...

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Entrepreneurial Challenge DISCOVER

Entrepreneurial Challenge DISCOVER

Second Prime Minister’s Entrepreneurial Challenge DISCOVER – Prosperity through entrepreneurship; was organized by the Center of Innovation and Entrepreneurship in National University of Sciences and Technology (NUST) Pakistan. Over 1600 students from across 55 universities of Pakistan participated in the competition to showcase 376 brilliantly conceived ideas. After the registration, there started a rigorous process of training, mentoring and selection of the best among the participating teams for the final stage of the competition. In the Grand Finale, the top ten teams, presented their innovative ideas before a jam-packed audience. These included business plans related to biotechnology, electronics, power generation, agriculture, transport, health, food,...

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