Blog Archives

Why Use Algocyte?*

24/8/2020

We asked patients and doctors and this is what they said

Patients

Algocyte is helping change how frequently and where people are monitored and get tested, but most people (89%) are still at high risk of infection from travelling to GP practices and hospitals to get their blood testing done, especially those requiring regular monitoring (30%).

Patients surveyed about Algocyte found that getting a regular appointment for a blood test was too long (at least a week on average)

which together with the time they had to wait for their blood test results amounted to up to two more weeks in total.

A majority of patients say yes to finger-pricking over the alternatives

Patients find the main features of Algocyte useful.

Practitioners

The number of tests and hours that doctors and nurses request and spend on blood testing is significant

Enabled by the responsible AI-powered capabilities of Algocyte, doctors found that they could save appointments and spend several hours a week on other activities, including providing more time and greater quality of care to patients.

There was a clear consensus on time-saving and usefulness of results and analytics in a remote app and solution for rapid remote blood testing.

* Data collected from a survey independently conducted and answered by 28 people including doctors (all levels), paramedics, nurses, and patients by the Medici Medical Centre clinic in Luton on June 11, 2020, a GP practice with over 15,000 patients.

OIA MEMBERS DELIVER invited talk on oia's cutting-edge A.I. at automata 2020

15/8/2020

OIA's CTO Dr. Jürgen Riedel and Senior AI Researcher Dr. Santiago Hernández-Orozco delivered an invited technical talk at the international conference AUTOMATA 2020, the 26th International Workshop on Cellular Automata and Discrete Complex Systems, one of the most reputable conferences in the field.

Jürgen and Santiago explained some of the most fundamental technical aspects behind OIA's A.I. and Machine Learning approaches to transforming medicine from simple statistical pattern-matching to causal diagnostics, and how OIA's methods and technology give it an edge when it comes to robustness (e.g. to perturbations and interventions), generalisation (over-fitting avoidance) and explainability, features of what we call a responsible A.I. approach to applications in healthcare.

According to a survey conducted by London venture capital firm MMC, 40% of European startups that are classified as A.I. companies don't actually use artificial intelligence in a way that is “material” to their businesses. Another percentage are startups or companies that adopt AI, but very few innovate in AI as much as in its domain of application, as OIA with its group of AI leaders and pioneers does.

Here are some of OIA's most recent papers published in some of the top journals in the fields of AI, automata and molecular biology research:

Rule Primality, Minimal Generating Sets and Turing-Universality in the Causal Decomposition of Elementary Cellular Automata
Journal of Cellular Automata, vol. 13, pp. 479–497, 2018.
Causal Deconvolution by Algorithmic Generative Models
Nature Machine Intelligence, vol 1, pages 58–66, 2019.
Training-free Measures Based on Algorithmic Probability Identify High Nucleosome Occupancy in DNA Sequences
Nucleic Acids Research, gkz750, 2019.
An Algorithmic Information Calculus for Causal Discovery and Reprogramming Systems
iScience, S2589-0042(19)30270-6, 2019.
Algorithmic Probability-guided Machine Learning On Non-differentiable Spaces
arXiv:1910.02758v2 Machine Learning (cs.LG), 2020.