I've been tracking my own health data for quite some time now, blood tests, sleep, how I feel, diet. The problem was always that everything lived in separate silos inside a basic CMS I have built. Some time ago I started taking a master's degree, in nature science and I started studying statistics and while looking for some project to exercise and apply what I was learning I decided to resurrect my health cms project try to tie some basic analysis in it, but then rabbit hole digging began ahah. I began reading papers on biomarker correlations, EWMA smoothing, allostatic load. At some point I thought: what if I actually modeled this properly?
So I refactored my whole app into something a bit more modern, thanks to AI helping me during this process and now I integrated some of the most interesting findings I found in the papers (linked in the readme of the repo). I named it Synaps, because it's about connections and integrated system, and so far this is what it can do:
- Extracts biomarkers from lab report PDFs/photos via Claude vision
- Tracks sleep, diet, activity, wellbeing, body composition, medications, environment (Open-Meteo, I'm mad about this stuff)
- Computes continuous-time EWMA, z-scores, trend detection, and within-person Pearson correlations across domains with lag 0–2 days, autocorrelation correction, and Benjamini-Hochberg FDR
- Builds a typed knowledge graph (biomarkers, conditions, lifestyle, environment) with AI-inferred edges validated against the statistical correlations
- Estimates allostatic load from a 17-cohort IPD meta-analysis consensus
Everything runs on your own hardware. Install is a single curl | bash. No cloud, no subscription, you can also use it without AI and just analyse all your reports manually, but you lose some important feature.
In the next future I would like to also test how it perform with local models using ollama, but this is what I have been using for my self and I like it
For remote acces I use NetBird, I think is the best and secure option to not expose stuff directly on the web and put all your resources under a vpn. Is super easy to setup and it supports also sso with 2fa
I wonder with which companies they partner for those deliveries. Maybe they went with Japan's biggest courier or well, I'm sure they don't do it in house...
you are just used to google, it doesn't mean it's better than others. I switched to DDG several years ago, now I'm used to it. Sometimes when I go back to google i think the results are just bad, because I'm used to how DDG works now. Google just shows you always what you'd like to see, this is not good at all, you just live inside a walled garden.
Worth emphasising IMO. People are conditioned to using Google and its quirks, that can make alternatives engines a little less intuitive. Also they're often criticised for overrunning verticals with their own offerings. My favourite example being celebritynetworth.
Beyond 10 blue links, certain niches organic results have been pushed down the page and placed under G specific results (when I say certain, nowadays it's most).
Celebritynetworth is an example of this where a site had some unique content, G apparently realised that lots of people search for such stuff, asked the owner for an API and then eventually scraped it. A rough version of events, more details below.
There are lots of examples of well performing sites/niches where similar has happened.
I embarked on this experience of dedicating my some of time to children, totally free of charge. I believe that we must give back our fortune somehow. This is my way.
I just stopped working for other people/company, I only work for myself.
Any kind of anxiety disappeared just after I learned how to survive by myself.
So I refactored my whole app into something a bit more modern, thanks to AI helping me during this process and now I integrated some of the most interesting findings I found in the papers (linked in the readme of the repo). I named it Synaps, because it's about connections and integrated system, and so far this is what it can do: - Extracts biomarkers from lab report PDFs/photos via Claude vision - Tracks sleep, diet, activity, wellbeing, body composition, medications, environment (Open-Meteo, I'm mad about this stuff) - Computes continuous-time EWMA, z-scores, trend detection, and within-person Pearson correlations across domains with lag 0–2 days, autocorrelation correction, and Benjamini-Hochberg FDR - Builds a typed knowledge graph (biomarkers, conditions, lifestyle, environment) with AI-inferred edges validated against the statistical correlations - Estimates allostatic load from a 17-cohort IPD meta-analysis consensus
Everything runs on your own hardware. Install is a single curl | bash. No cloud, no subscription, you can also use it without AI and just analyse all your reports manually, but you lose some important feature.
In the next future I would like to also test how it perform with local models using ollama, but this is what I have been using for my self and I like it
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